Oracle University Podcast

Join hosts Lois Houston and Nikita Abraham, along with Principal AI/ML Instructor Himanshu Raj, as they discuss the transformative world of Generative AI. Together, they uncover the ways in which generative AI agents are changing the way we interact with technology, automating tasks and delivering new possibilities.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead of Editorial Services.   Nikita: Hi everyone! Last week was Part 2 of our conversation on core AI concepts, where we went over the basics of data science. In Part 3 today, we’ll look at generative AI and gen AI agents in detail. To help us with that, we have Himanshu Raj, Principal AI/ML Instructor. Hi Himanshu, what’s the difference between traditional AI and generative AI?  01:01 Himanshu: So until now, when we talked about artificial intelligence, we usually meant models that could analyze information and make decisions based on it, like a judge who looks at evidence and gives a verdict. And that's what we call traditional AI that's focused on analysis, classification, and prediction.  But with generative AI, something remarkable happens. Generative AI does not just evaluate. It creates. It's more like a storyteller who uses knowledge from the past to imagine and build something brand new. For example, instead of just detecting if an email is spam, generative AI could write an entirely new email for you.  Another example, traditional AI might predict what a photo contains. Generative AI, on the other hand, creates a brand-new photo based on description. Generative AI refers to artificial intelligence models that can create entirely new content, such as text, images, music, code, or video that resembles human-made work.  Instead of simple analyzing or predicting, generative AI produces something original that resembles what a human might create.   02:16 Lois: How did traditional AI progress to the generative AI we know today?  Himanshu: First, we will look at small supervised learning. So in early days, AI models were trained on small labeled data sets. For example, we could train a model with a few thousand emails labeled spam or not spam. The model would learn simple decision boundaries. If email contains, "congratulations," it might be spam. This was efficient for a straightforward task, but it struggled with anything more complex.  Then, comes the large supervised learning. As the internet exploded, massive data sets became available, so millions of images, billions of text snippets, and models got better because they had much more data and stronger compute power and thanks to advances, like GPUs, and cloud computing, for example, training a model on millions of product reviews to predict customer sentiment, positive or negative, or to classify thousands of images in cars, dogs, planes, etc.  Models became more sophisticated, capturing deeper patterns rather than simple rules. And then, generative AI came into the picture, and we eventually reached a point where instead of just classifying or predicting, models could generate entirely new content.  Generative AI models like ChatGPT or GitHub Copilot are trained on enormous data sets, not to simply answer a yes or no, but to create outputs that look and feel like human made. Instead of judging the spam or sentiment, now the model can write an article, compose a song, or paint a picture, or generate new software code.  03:55 Nikita: Himanshu, what motivated this sort of progression?   Himanshu: Because of the three reasons. First one, data, we had way more of it thanks to the internet, smartphones, and social media. Second is compute. Graphics cards, GPUs, parallel computing, and cloud systems made it cheap and fast to train giant models.  And third, and most important is ambition. Humans always wanted machines not just to judge existing data, but to create new knowledge, art, and ideas.   04:25 Lois: So, what’s happening behind the scenes? How is gen AI making these things happen?  Himanshu: Generative AI is about creating entirely new things across different domains. On one side, we have large language models or LLMs.  They are masters of generating text conversations, stories, emails, and even code. And on the other side, we have diffusion models. They are the creative artists of AI, turning text prompts into detailed images, paintings, or even videos.  And these two together are like two different specialists. The LLM acts like a brain that understands and talks, and the diffusion model acts like an artist that paints based on the instructions. And when we connect these spaces together, we create something called multimodal AI, systems that can take in text and produce images, audio, or other media, opening a whole new range of possibilities.  It can not only take the text, but also deal in different media options. So today when we say ChatGPT or Gemini, they can generate images, and it's not just one model doing everything. These are specialized systems working together behind the scenes.  05:38 Lois: You mentioned large language models and how they power text-based gen AI, so let’s talk more about them. Himanshu, what is an LLM and how does it work?  Himanshu: So it's a probabilistic model of text, which means, it tries to predict what word is most likely to come next based on what came before.  This ability to predict one word at a time intelligently is what builds full sentences, paragraphs, and even stories.  06:06 Nikita: But what’s large about this? Why’s it called a large language model?   Himanshu: It simply means the model has lots and lots of parameters. And think of parameters as adjustable dials the model fine tuned during learning.  There is no strict rule, but today, large models can have billions or even trillions of these parameters. And the more the parameters, more complex patterns, the model can understand and can generate a language better, more like human.  06:37 Nikita: Ok… and image-based generative AI is powered by diffusion models, right? How do they work?  Himanshu: Diffusion models start with something that looks like pure random noise.  Imagine static on an old TV screen. No meaningful image at all. From there, the model carefully removes noise step by step to create something more meaningful and think of it like sculpting a statue. You start with a rough block of stone and slowly, carefully you chisel away to reveal a beautiful sculpture hidden inside.  And in each step of this process, the AI is making an educated guess based on everything it has learned from millions of real images. It's trying to predict.   07:24 Stay current by taking the 2025 Oracle Fusion Cloud Applications Delta Certifications. This is your chance to demonstrate your understanding of the latest features and prove your expertise by obtaining a globally recognized certification, all for free! Discover the certification paths, use the resources on MyLearn to prepare, and future-proof your skills. Get started now at mylearn.oracle.com.  07:53 Nikita: Welcome back! Himanshu, for most of us, our experience with generative AI is with text-based tools like ChatGPT. But I’m sure the uses go far beyond that, right? Can you walk us through some of them?  Himanshu: First one is text generation. So we can talk about chatbots, which are now capable of handling nuanced customer queries in banking travel and retail, saving companies hours of support time. Think of a bank chatbot helping a customer understand mortgage options or virtual HR Assistant in a large company, handling leave request. You can have embedding models which powers smart search systems.  Instead of searching by keywords, businesses can now search by meaning. For instance, a legal firm can search cases about contract violations in tech and get semantically relevant results, even if those exact words are not used in the documents.  The third one, for example, code generation, tools like GitHub Copilot help developers write boilerplate or even functional code, accelerating software development, especially in routine or repetitive tasks. Imagine writing a waveform with just a few prompts.  The second application, is image generation. So first obvious use is art. So designers and marketers can generate creative concepts instantly. Say, you need illustrations for a campaign on future cities. Generative AI can produce dozens of stylized visuals in minutes.  For design, interior designers or architects use it to visualize room layouts or design ideas even before a blueprint is finalized. And realistic images, retail companies generate images of people wearing their clothing items without needing real models or photoshoots, and this reduces the cost and increase the personalization.  Third application is multimodal systems, and these are combined systems that take one kind of input or a combination of different inputs and produce different kind of outputs, or can even combine various kinds, be it text image in both input and output.  Text to image It's being used in e-commerce, movie concept art, and educational content creation. For text to video, this is still in early days, but imagine creating a product explainer video just by typing out t

In this episode, Lois Houston and Nikita Abraham continue their discussion on AI fundamentals, diving into Data Science with Principal AI/ML Instructor Himanshu Raj. They explore key concepts like data collection, cleaning, and analysis, and talk about how quality data drives impactful insights.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ---------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast. I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me today is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! Last week, we began our exploration of core AI concepts, specifically machine learning and deep learning. I’d really encourage you to go back and listen to the episode if you missed it.   00:52 Lois: Yeah, today we’re continuing that discussion, focusing on data science, with our Principal AI/ML Instructor Himanshu Raj.  Nikita: Hi Himanshu! Thanks for joining us again. So, let’s get cracking! What is data science?  01:06 Himanshu: It's about collecting, organizing, analyzing, and interpreting data to uncover valuable insights that help us make better business decisions. Think of data science as the engine that transforms raw information into strategic action.  You can think of a data scientist as a detective. They gather clues, which is our data. Connect the dots between those clues and ultimately solve mysteries, meaning they find hidden patterns that can drive value.  01:33 Nikita: Ok, and how does this happen exactly?  Himanshu: Just like a detective relies on both instincts and evidence, data science blends domain expertise and analytical techniques. First, we collect raw data. Then we prepare and clean it because messy data leads to messy conclusions. Next, we analyze to find meaningful patterns in that data. And finally, we turn those patterns into actionable insights that businesses can trust.  02:00 Lois: So what you’re saying is, data science is not just about technology; it's about turning information into intelligence that organizations can act on. Can you walk us through the typical steps a data scientist follows in a real-world project?  Himanshu: So it all begins with business understanding. Identifying the real problem we are trying to solve. It's not about collecting data blindly. It's about asking the right business questions first. And once we know the problem, we move to data collection, which is gathering the relevant data from available sources, whether internal or external.  Next one is data cleaning. Probably the least glamorous but one of the most important steps. And this is where we fix missing values, remove errors, and ensure that the data is usable. Then we perform data analysis or what we call exploratory data analysis.  Here we look for patterns, prints, and initial signals hidden inside the data. After that comes the modeling and evaluation, where we apply machine learning or deep learning techniques to predict, classify, or forecast outcomes. Machine learning, deep learning are like specialized equipment in a data science detective's toolkit. Powerful but not the whole investigation.  We also check how good the models are in terms of accuracy, relevance, and business usefulness. Finally, if the model meets expectations, we move to deployment and monitoring, putting the model into real world use and continuously watching how it performs over time.  03:34 Nikita: So, it’s a linear process?  Himanshu: It's not linear. That's because in real world data science projects, the process does not stop after deployment. Once the model is live, business needs may evolve, new data may become available, or unexpected patterns may emerge.  And that's why we come back to business understanding again, defining the questions, the strategy, and sometimes even the goals based on what we have learned. In a way, a good data science project behaves like living in a system which grows, adapts, and improves over time. Continuous improvement keeps it aligned with business value.   Now, think of it like adjusting your GPS while driving. The route you plan initially might change as new traffic data comes in. Similarly, in data science, new information constantly help refine our course. The quality of our data determines the quality of our results.   If the data we feed into our models is messy, inaccurate, or incomplete, the outputs, no matter how sophisticated the technology, will be also unreliable. And this concept is often called garbage in, garbage out. Bad input leads to bad output.  Now, think of it like cooking. Even the world's best Michelin star chef can't create a masterpiece with spoiled or poor-quality ingredients. In the same way, even the most advanced AI models can't perform well if the data they are trained on is flawed.  05:05 Lois: Yeah, that's why high-quality data is not just nice to have, it’s absolutely essential. But Himanshu, what makes data good?   Himanshu: Good data has a few essential qualities. The first one is complete. Make sure we aren't missing any critical field. For example, every customer record must have a phone number and an email. It should be accurate. The data should reflect reality. If a customer's address has changed, it must be updated, not outdated. Third, it should be consistent. Similar data must follow the same format. Imagine if the dates are written differently, like 2024/04/28 versus April 28, 2024. We must standardize them.   Fourth one. Good data should be relevant. We collect only the data that actually helps solve our business question, not unnecessary noise. And last one, it should be timely. So data should be up to date. Using last year's purchase data for a real time recommendation engine wouldn't be helpful.  06:13 Nikita: Ok, so ideally, we should use good data. But that’s a bit difficult in reality, right? Because what comes to us is often pretty messy. So, how do we convert bad data into good data? I’m sure there are processes we use to do this.  Himanshu: First one is cleaning. So this is about correcting simple mistakes, like fixing typos in city names or standardizing dates.  The second one is imputation. So if some values are missing, we fill them intelligently, for instance, using the average income for a missing salary field. Third one is filtering. In this, we remove irrelevant or noisy records, like discarding fake email signups from marketing data. The fourth one is enriching. We can even enhance our data by adding trusted external sources, like appending credit scores from a verified bureau.  And the last one is transformation. Here, we finally reshape data formats to be consistent, for example, converting all units to the same currency. So even messy data can become usable, but it takes deliberate effort, structured process, and attention to quality at every step.  07:26 Oracle University’s Race to Certification 2025 is your ticket to free training and certification in today’s hottest technology. Whether you’re starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That’s education.oracle.com/race-to-certification-2025. 08:10 Nikita: Welcome back! Himanshu, we spoke about how to clean data. Now, once we get high-quality data, how do we analyze it?  Himanshu: In data science, there are four primary types of analysis we typically apply depending on the business goal we are trying to achieve.  The first one is descriptive analysis. It helps summarize and report what has happened. So often using averages, totals, or percentages. For example, retailers use descriptive analysis to understand things like what was the average customer spend last quarter? How did store foot traffic trend across months?  The second one is diagnostic analysis. Diagnostic analysis digs deeper into why something happened. For example, hospitals use this type of analysis to find out, for example, why a certain department has higher patient readmission rates. Was it due to staffing, post-treatment care, or patient demographics?  The third one is predictive analysis. Predictive analysis looks forward, trying to forecast future outcomes based on historical patterns. For example, energy companies predict future electricity demand, so they can better manage resources and avoid shortages. And the last one is prescriptive analysis. So it does not just predict. It recommends specific actions to take.  So logistics and supply chain companies use prescriptive analytics to suggest the most efficient delivery routes or warehouse stocking strategies based on traffic patterns, order volume, and delivery deadlines.   09:42 Lois: So really, we’re using data science to solve everyday problems. Can you walk us through some practical examples of how it’s being applied?  Himanshu: The first one is predictive maintenance. It is done in manufacturing a lot. A factory collects real time sensor data from machines. Data scientists first clean and organize this massive data stream, explore patterns of past failures, and design predictive models.  The goal is not just to predict breakdowns but to optimize maintenance schedules, reducing downtime and saving milli

In this episode, hosts Lois Houston and Nikita Abraham, together with Senior Cloud Engineer Nick Commisso, break down the basics of artificial intelligence (AI). They discuss the differences between Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI), and explore the concepts of machine learning, deep learning, and generative AI. Nick also shares examples of how AI is used in everyday life, from navigation apps to spam filters, and explains how AI can help businesses cut costs and boost revenue.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/252500   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Hello and welcome to the Oracle University Podcast. I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hi everyone! Welcome to a new season of the podcast. I’m so excited about this one because we’re going to dive into the world of artificial intelligence, speaking to many experts in the field. Nikita: If you've been listening to us for a while, you probably know we’ve covered AI from a bunch of different angles. But this time, we’re dialing it all the way back to basics. We wanted to create something for the absolute beginner, so no jargon, no assumptions, just simple conversations that anyone can follow. 01:08 Lois: That’s right, Niki. You don’t need to have a technical background or prior experience with AI to get the most out of these episodes. In our upcoming conversations, we’ll break down the basics of AI, explore how it's shaping the world around us, and understand its impact on your business. Nikita: The idea is to give you a practical understanding of AI that you can use in your work, especially if you’re in sales, marketing, operations, HR, or even customer service.  01:37 Lois: Today, we’ll talk about the basics of AI with Senior Cloud Engineer Nick Commisso. Hi Nick! Welcome back to the podcast. Can you tell us about human intelligence and how it relates to artificial intelligence? And within AI, I know we have Artificial General Intelligence, or AGI, and Artificial Narrow Intelligence, or ANI. What’s the difference between the two? Nick: Human intelligence is the intellectual capability of humans that allow us to learn new skills through observation and mental digestion, to think through and understand abstract concepts and apply reasoning, to communicate using language and understand non-verbal cues, such as facial expressions, tone variation, body language. We can handle objections and situations in real time, even in a complex setting. We can plan for short and long-term situations or projects. And we can create music, art, or invent something new or have original ideas. If machines can replicate a wide range of human cognitive abilities, such as learning, reasoning, or problem solving, we call it artificial general intelligence.  Now, AGI is hypothetical for now, but when we apply AI to solve problems with specific, narrow objectives, we call it artificial narrow intelligence, or ANI. AGI is a hypothetical AI that thinks like a human. It represents the ultimate goal of artificial intelligence, which is a system capable of chatting, learning, and even arguing like us. If AGI existed, it would take the form like a robot doctor that accurately diagnoses and comforts patients, or an AI teacher that customizes lessons in real time based on each student's mood, pace, and learning style, or an AI therapist that comprehends complex emotions and provides empathetic, personalized support. ANI, on the other hand, focuses on doing one thing really well. It's designed to perform specific tasks by recognizing patterns and following rules, but it doesn't truly understand or think beyond its narrow scope. Think of ANI as a specialist. Your phone's face ID can recognize you instantly, but it can't carry on a conversation. Google Maps finds the best route, but it can't write you a poem. And spam filters catch junk mail, but it can't make you coffee. So, most of the AI you interact with today is ANI. It's smart, efficient, and practical, but limited to specific functions without general reasoning or creativity. 04:22 Nikita: Ok then what about Generative AI?  Nick: Generative AI is a type of AI that can produce content such as audio, text, code, video, and images. ChatGPT can write essays, but it can't fact check itself. DALL-E creates art, but it doesn't actually know if it's good. Or AI song covers can create deepfakes like Drake singing "Baby Shark."  04:47 Lois: Why should I care about AI? Why is it important? Nick: AI is already part of your everyday life, often working quietly in the background. ANI powers things like navigation apps, voice assistants, and spam filters. Generative AI helps create everything from custom playlists to smart writing tools. And while AGI isn't here yet, it's shaping ideas about what the future might look like. Now, AI is not just a buzzword, it's a tool that's changing how we live, work, and interact with the world. So, whether you're using it or learning about it or just curious, it's worth knowing what's behind the tech that's becoming part of everyday life.  05:32 Lois: Nick, whenever people talk about AI, they also throw around terms like machine learning and deep learning. What are they and how do they relate to AI? Nick: As we shared earlier, AI is the ability of machines to imitate human intelligence. And Machine Learning, or ML, is a subset of AI where the algorithms are used to learn from past data and predict outcomes on new data or to identify trends from the past. Deep Learning, or DL, is a subset of machine learning that uses neural networks to learn patterns from complex data and make predictions or classifications. And Generative AI, or GenAI, on the other hand, is a specific application of DL focused on creating new content, such as text, images, and audio, by learning the underlying structure of the training data.  06:24 Nikita: AI is often associated with key domains like language, speech, and vision, right? So, could you walk us through some of the specific tasks or applications within each of these areas? Nick: Language-related AI tasks can be text related or generative AI. Text-related AI tasks use text as input, and the output can vary depending on the task. Some examples include detecting language, extracting entities in a text, extracting key phrases, and so on.  06:54 Lois: Ok, I get you. That’s like translating text, where you can use a text translation tool, type your text in the box, choose your source and target language, and then click Translate. That would be an example of a text-related AI task. What about generative AI language tasks? Nick: These are generative, which means the output text is generated by the model. Some examples are creating text, like stories or poems, summarizing texts, and answering questions, and so on. 07:25 Nikita: What about speech and vision? Nick: Speech-related AI tasks can be audio related or generative AI. Speech-related AI tasks use audio or speech as input, and the output can vary depending on the task. For example, speech to text conversion, speaker recognition, or voice conversion, and so on. Generative AI tasks are generative, i.e., the output audio is generated by the model (for example, music composition or speech synthesis). Vision-related AI tasks can be image related or generative AI. Image-related AI tasks use an image as the input, and the output depends on the task. Some examples are classifying images or identifying objects in an image. Facial recognition is one of the most popular image-related tasks that's often used for surveillance and tracking people in real time. It's used in a lot of different fields, like security and biometrics, law enforcement, entertainment, and social media. For generative AI tasks, the output image is generated by the model. For example, creating an image from a textual description or generating images of specific style or high resolution, and so on. It can create extremely realistic new images and videos by generating original 3D models of objects, such as machine, buildings, medications, people and landscapes, and so much more. 08:58 Lois: This is so fascinating. So, now we know what AI is capable of. But Nick, what is AI good at? Nick: AI frees you to focus on creativity and more challenging parts of your work. Now, AI isn't magic. It's just very good at certain tasks. It handles work that's repetitive, time consuming, or too complex for humans, like processing data or spotting patterns in large data sets.  AI can take over routine tasks that are essential but monotonous. Examples include entering data into spreadsheets, processing invoices, or even scheduling meetings, freeing up time for more meaningful work. AI can support professionals by extending their abilities. Now, this includes tools like AI-assisted coding for developers, real-time language translation for travelers or global teams, and advanced image analysis to help doctors interpret medical scans much more accurately. 10:00 Nikita: And what would you say is AI's sweet spot? Nick: That would be tasks that are both doable and valuable. A few examples of tasks that are feasible technically and have business value are things like predicting equipment failure. This saves downtime and the loss of bu

In this episode, hosts Lois Houston and Nikita Abraham welcome back Cloud Delivery Lead Sarah Mahalik for a detailed tour of the four pillars of Oracle Fusion Cloud Applications: ERP, HCM, SCM, and CX.   Discover how Oracle weaves AI, analytics, and automation into every layer of enterprise operations. Plus, learn how Oracle Modern Best Practice is redefining digital workflows.   Oracle Fusion Cloud Applications: Process Essentials https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-hcm/146870 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundations-enterprise-resource-planning-erp/146928/241047 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-scm/146938 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-cx/146972   Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------------- Episode Transcript:   00:00   Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started!   00:25   Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and joining me is Nikita Abraham, Team Lead: Editorial Services.     Nikita: Hi everyone! Last week, we spoke about Oracle Cloud Apps and the Redwood design system. Today, we’ll take a closer look at the four key pillars of Oracle Cloud Apps.    Lois: And we’re so excited to have Sarah Mahalik back with us. Sarah is a Cloud Delivery Lead here at Oracle. Hi Sarah! In the last episode, we briefly spoke about the various Oracle Cloud Apps offerings and their capabilities. For anyone who missed that episode, can you give us a quick introduction?   01:06   Sarah: Oracle Cloud Applications is an incredibly broad suite that covers many of the most important business functions, from Human Capital Management, Supply Chain Management, to Enterprise Resource Planning and Customer Experience. The products in the Oracle Fusion Cloud Applications suite are organized by functional groups or pillars. All of these applications sit on Oracle Cloud Infrastructure, a foundation built from scratch to support mission-critical applications.    Oracle Fusion Applications deliver a single source of truth, enabling quick responses to disruptions and market opportunities. With unified data and consistent business rules, teams can build streamlined end-to-end processes, access real time analytics, and make faster data-driven decisions for improved outcomes.   01:52   Nikita: Ok, let’s actually get into each of these areas. I think we can start with Human Capital Management.   Sarah: Oracle Human Capital Management is an end-to-end solution that allows you to manage all aspects of people data from hire to retire. It all starts with recruiting, or requisitions are used to advertise vacant positions, and candidates are managed through the hiring process. After recruitment, successful candidates are transferred to the human resources module.   You can configure the organization structure to mirror that of your business. And this allows for easy reorganization whenever the structure changes. People data is a staple element of HCM. Therefore, as part of this product, an HR specialist can manage everything about the employee life cycle, including promotions, transfers, general assignment changes, and terminations.   A robust self-service offering allows employees and managers to take ownership and responsibility for the data pertaining to themselves and their teams. By removing the burden of simple data processing from the HR specialists, it not only eases the pressure on the HR department but allows them to concentrate on more specialized tasks.   03:00   Lois: And how are the core products of HCM categorized?   Sarah: The core products of Human Capital Management are categorized into four main groupings according to their logical purpose. First up, we have our human resources. This grouping includes the elements for implementing and maintaining the enterprise and workforce structure and employee life cycle data. This is where you would configure the organization structure as well as manage an employee's data from the HR specialist point of view. In addition, modules such as benefits, work life, workforce modeling and planning, and advanced HCM controls also sit within this category.   This brings us to talent management. This category is one of the largest because it includes recruiting, learning, goals and performance management, career development, succession planning, talent reviews, and compensation. In addition to that, dynamic skills and opportunity marketplace are also included in this grouping. Within workforce management, you'll find absence management and time and labor.   These naturally sit together because most organizations that implement both configure it so that an employee can enter both work time and absences on a time card, instead of having to visit two different entry points. You'll also find workforce health and safety here. And finally, payroll. All aspects of payroll are included here, whether you're simply using global payroll or localizations, such as UK, Canada, and Mexico.   It also encompasses payroll interface for those organizations that run their payroll from another system, and just need to extract and migrate the relevant data from Fusion HCM Cloud. When talking about HCM systems, we cannot forget the employee self-service aspect of the product. For this, there's an employee experience module called Oracle Me. Here you'll find options, such as HCM communicate, touchpoints, journeys, HR help desk, and Oracle digital assistant.   All of these combined enable an employee to take control and ownership of their own data, and use the many self-help options to get the information they need quickly and efficiently. In order to control how the system behaves and how users interact with it and perform the various processes, there are configuration options. These options allow organizations to define such things as the user experience, workflows, and approval policies based on their business requirements. And to meet the constant need for reporting, there's analytics, planning, and data modeling.   And in addition to all of that, you can use configuration options, such as extensibility, integration, or import and extracts, security, and adaptive intelligence to help enhance the system and have it working and looking the way you need. Of course, much of these latter configuration items are not exclusive to HCM but are available for the Oracle Fusion Cloud as a whole.   05:47   Lois: That’s great. Ok, let’s move on to Oracle Enterprise Resource Planning, or ERP.   Sarah: This is a complete modern Cloud ERP suite that provides your teams with advanced capabilities, such as AI, to automate the manual processes that slow them down, analytics to react to market shifts in real time, and automatic updates to stay current and gain a competitive advantage.   Oracle Cloud ERP automates the entire Record to Report process and provides a common repository of information for global financial reporting and compliance. Within ERP, we have the broadest and deepest suite offering everything you need, from financials, project management, enterprise performance management, risk management and compliance, and analytics.    06:34   Nikita: Sarah, could you break down the different modules within ERP?   Sarah: First, we have Financials, which is a global financial platform that connects and automates your financial management processes, including payables, receivables, fixed assets, expenses, and reporting for a clear view into your total financial health. Oracle Project Management offers a single project cloud solution designed to help you gain a complete picture of your organization's project finances and operations. It's seamlessly integrated across the enterprise with the Oracle Fusion Cloud ERP, HCM, and SCM applications.   Oracle Fusion Cloud Enterprise Performance Management, or EPM, helps you model and plan across finance, HR, supply chain and sales, streamline the financial close process, and drive better decisions. Oracle Fusion Cloud Risk Management and Compliance is a security and audit solution that controls user access to your Oracle Cloud ERP financial data, monitors user activity, and makes it easier to meet compliance regulations through automation.   Oracle Risk Management Compliance uses AI and ML to strengthen financial controls to help prevent cash leaks, enforce audit, and protect against emerging risks, saving you hours of manual work. Oracle Analytics for Cloud ERP complements the embedded analytics in Cloud ERP to provide pre-packaged use cases, predictive analysis, and KPIs based on variance analysis and historical trends.    08:06   Lois: And what about Supply Chain Management?   Sarah: Oracle Supply Chain Management empowers organizations to plan, source, make, deliver, and service goods with agility and resilience. It offers a solution that integrates advanced capabilities, such as AI/ML and blockchain, to optimize the supply chain life cycle from start to finish.   08:31   Adopting a multicloud strategy is a big step towards future-proofing your business and we’re here to help you navigate this complex landscape. With our suite of courses, you'll gain insights into network connectivity, security protocols, and the considerations of working across different cloud platforms. Start your journey today to multicloud today by visiting myle

Join hosts Lois Houston and Nikita Abraham, along with Cloud Delivery Lead Sarah Mahalik, as they unpack the core pillars of Oracle Fusion Cloud Applications—ERP, HCM, SCM, and CX.   Learn how Oracle’s SaaS model, Redwood UX, and built-in AI are reshaping business productivity, adaptability, and user experience. From quarterly updates to advanced AI agents, discover how Oracle delivers agility, lower costs, and smarter decision-making across departments.   Oracle Fusion Cloud Applications: Process Essentials https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-hcm/146870 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundations-enterprise-resource-planning-erp/146928/241047 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-scm/146938 https://mylearn.oracle.com/ou/course/oracle-fusion-cloud-applications-foundation-cx/146972   Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. -------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I’m Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs.  Lois: Hi everyone! In our last two episodes, we explored the Oracle Cloud Success Navigator platform. This week and next, we’re diving into Oracle Fusion Cloud Applications with Sarah Mahalik, a Cloud Delivery Lead here at Oracle. We’ll ask Sarah about Oracle’s cloud apps suite, the Redwood design system, and also look at some of Oracle’s AI capabilities.  01:02 Nikita: Yeah, let’s jump right in. Hi Sarah! How does Oracle approach the SaaS model? Sarah: Oracle's Cloud Applications suite is a complete enterprise cloud designed to modernize your business. Our cloud suite of SaaS applications, which includes Enterprise Resource Planning, or ERP, Supply Chain Management, or SCM, Human Capital Management, or HCM, and Customer Experience, or CX, brings consistent processes and a single source of truth across the most important business functions.  At Oracle, we own all of the technology stacks that power our suite of cloud applications. Oracle Cloud Applications are built on Oracle Cloud Infrastructure and ensure the performance, resiliency, and security that enterprises need. Your business no longer needs to worry about maintaining a data center, hardware, operating systems, database, network, or all of the security. With deep integrations, a common data model, and a unified user interface, these applications help improve customer engagement, increase agility, and accelerate response to change. Oracle's Cloud Applications are updated quarterly with new features and improvements. These updates are based on our deep understanding of customer's functional needs, as well as modern technologies such as artificial intelligence, machine learning, blockchain, and digital assistants. Expectations for user experience only go up. Oracle's Redwood User Experience methodology ensures those expectations are matched and exceeded by including powerful and predictive search, a look and feel that actually helps users see what they need to in the order they need to see it, and by providing conversational and micro-interactions. Oracle, as a SaaS provider, puts the customer first by having enough dedicated resources to ensure zero downtime and increasing the speed of implementation by eliminating much of the hardware and software setup activity. 02:59 Nikita: What are the advantages of adopting Oracle Cloud Apps? Sarah: First off, Oracle provides automatic quarterly updates, and they're usable immediately. Customers can focus on leveraging the new functionality instead of spending cycles on installing it. There's much more accessibility because Oracle hosts the heavy part of the applications and customers access it via thin clients. The applications can be used from nearly anywhere and on a wide range of devices, including smartphones and tablets. Another great advantage is speed and agility. A lot of the benefits you see here result from Oracle's provider model. That means customers aren't spending time on customization, application testing, and report development. Instead, they work on the much lighter and faster tasks of configuration, validation, and leveraging embedded analytics. And finally, it's just better economics. Because of the pricing model, it is easy to compare an on-premises implementation cost. While upfront costs are almost always lower, overall operational costs and risk are usually lower as well. This translates to better total cost of ownership and improved overall economics and agility for your business. 04:10 Lois: Sarah, in your experience, why do customers love Oracle Cloud Apps? Sarah: At Oracle, we empower you with embedded AI that drives real breakthroughs in productivity and efficiency, helping you stay ahead of the curve. With the power of Oracle Cloud Infrastructure, you get the best of performance, security, and scalability, making it the perfect foundation for your business. Our modern user experience is intuitive and designed with your needs in mind, while our relentless innovation is focused on what truly matters to you. Above all, our commitment to your success is unwavering. We're here to support you every step of the way, ensuring you thrive and grow with Oracle. 04:49 Lois: Let’s talk about Oracle’s Redwood design system. What is it? And how does it enhance the user experience?  Sarah: Redwood is the name of Oracle's next-generation user experience. Redwood design system is a collection of prefabricated components, templates, and patterns to enable developers to quickly create very sophisticated and polished interactions that are upgrade safe. It provides a consumer grade-plus experience, where you have high-quality functionality that can be used across multiple devices. You have access to insightful data readily at your fingertips for quick access and decision making, with the option to personalize your application to create your own state of the art experience. Processes and entry time will now be more efficient and streamlined by having fewer clicks and faster downloads, which will lead to high productivity in areas that matter the most. The Redwood design is intelligent, meaning you have access to AI, where you will receive recommendations and guidance based on your preferences and business processes. It's also adaptable, allowing you to use the same tools to create new experiences by using the Business Rule Framework with modern UX components. Oracle's Redwood user experience will help you to be more productive, efficient, and engaged with a highly personalized experience. 06:11 Are you keen to stay ahead in today's fast-paced world? We’ve got your back! Each quarter, Oracle rolls out game-changing updates to its Fusion Cloud Applications. And to make sure you’re always in the know, we offer New Features courses that give you an insider’s look at all of the latest advancements. Don't miss out! Head over to mylearn.oracle.com to get started.  06:37 Nikita: Welcome back! Sarah, you said the Redwood design system is adaptable. Can you elaborate on what you mean by that?  Sarah: In a nutshell, this means that developers can extend their applications using the same development platform that Oracle Cloud Applications are built on. Oracle Visual Builder Studio is a robust application development platform that enables users to rapidly create and extend web, mobile, and progressive web interfaces using a visual development environment. It streamlines application development and reduces coding, while also providing flexibility and support for popular build and testing frameworks. With Oracle Visual Builder Studio, users can build apps for the web, create progressive web apps, and develop on-device mobile apps. The tool also offers access to REST services and allows for planning and managing development processes, as well as managing the code lifecycle. Additionally, Oracle Visual Builder Studio provides hosting for apps along with easy publishing and version management. Changes made using Visual Builder Studio are called Application Extensions.  Visual Builder Studio Express Mode has two key components: Business Rules and Constants. Use Business Rules, which is the Redwood equivalent to Transaction Design Studio for responsive pages, to leverage delivered best practices or create your own rules based on various criteria, such as country and business unit. Make fields and regions required or optional, read-only or editable, and show or hide fields in regions, depending on specific criteria. Use the various delivered Constants to customize your Redwood pages to best fit your specific business needs, such as hide the evaluation panel and connections or reorder the columns in the person search result table. 08:23 Lois: Sarah, here’s a question that's probably on everyone's mind—what about AI for Fusion Applications? Sarah: Oracle integrates AI into Fusion Applications, enabling faster, better decision making and empowering your workforce. With both classic and generative AI embedded, customers can access AI-driven insights seamlessly within their everyday software environment. In HCM, AI helps to automate routine tasks. It's also used to attract and manage talent more efficiently by doing things like reducing the time to hire and performing automatic skill matching for job vacancies. It also uses some

Hosts Lois Houston and Nikita Abraham continue their discussion with Mitchell Flinn, VP of Program Management for the CSS Platform, by exploring how Oracle Cloud Success Navigator helps teams align faster, reduce risk, and drive value.   Learn how built-in quality benchmarks, modern best practices, and Starter Configuration tools accelerate cloud adoption, and explore ways to stay ahead with a mindset of continuous innovation.   Oracle Cloud Success Navigator Essentials: https://mylearn.oracle.com/ou/course/oracle-cloud-success-navigator-essentials/147489/242186 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University and with joining me today is Nikita Abraham, Team Lead of Editorial Services.  Nikita: Hi everyone! In our last episode, we gave you a broad overview of the Oracle Cloud Success Navigator platform—what it is, how it works, and its key features and benefits. Today, we’re continuing that discussion with Mitchell Flinn. Mitchell is VP of Program Management for Oracle Cloud Success Navigator, and in this episode, we’re going to ask him to walk us through some of the core components of the platform that we couldn’t get into last week. 01:04 Lois: Right, Niki. Hi Mitchell! You spoke a little about Cloud Quality Standards in our last episode. But how do they contribute or align with the vision of Oracle Cloud Success Navigator?  Mitchell: The vision for Navigator is to support customers throughout every phase of their cloud journey, providing timely advice to help improve outcomes to reduce cost and increase overall value. This model is driven through Oracle Cloud Quality Standards. These standards are intended to improve the transparency and collaboration between customer, partner, and Oracle members of a project. This is a project blueprint to include the ability for business and IT users to align on project coordination, expectations, and ultimately drive tighter alignment. Tracking key milestones and activities can help visualize and measure progress. You can build assessments and help answer questions so that at the right time, you have the right resources to make the right decisions for an organization. Cloud Quality Standards represent the key milestone dates and accomplishments along the journey. You can leverage these to increase project transparency, reduce risk, and increase the overall collaboration. Cloud Quality Standards are proactive list of must haves leveraged by customers, partners, and Oracle. They're a collection of knowledge and lessons learned from thousands of implementations globally. Cloud Quality Standards are partner agnostic and complimentary to all SI methodologies and tool sets. And they've been identified to address delivery issues before they happen and reduce the risk of implementations. 02:34 Lois: Ok, and a crucial component of Oracle Cloud Success Navigator is Oracle Modern Best Practice, or OMBP, right? Can you tell us more about what this is?  Mitchell: Oracle Modern Best Practices are based on distilled knowledge of our customers' needs gained from 10,000 successful delivery projects. They illustrate the business process components and their optimization to take advantage of the latest Oracle applications and technologies. Oracle Modern Best Practices comprise industry best practices and processes powered by Oracle technology. Engineered in Fusion Applications, OMBPs simplify and streamline workflows. They enable organizations to leverage modern, efficient, and scalable practices. As we align our assets with OMBPs, there's a stronger connection between global process owners and business process innovation within a customer's organization. 03:21 Nikita: And how do they help deliver end-to-end success for businesses?  Mitchell: An OMBP approach involves a digital business process, so evolving and adapting in real time to changing market dynamics. End-to-end across the organization, so we're breaking down silos and ensuring there's operational agility and a seamless collaboration between departments. We're leveraging emerging technologies, so utilizing AI, other cutting-edge technologies to automate routine tasks, enabling greater human creativity and unlocking new value and insights. And radically superior results, driving a significant improvement in measurable outcomes. OMBPs are dynamic, and when regularly updated, they meet evolving customer needs and technologies. They're trusted, tested, and validated by Oracle experts and publicly available and download on oracle.com. If you go to oracle.com and search modern best practice, you'll find more detailed introduction to Oracle Modern Best Practices. You'll also find Oracle Modern Best Practice business processes for domains such as ERP, EPM, Supply Chain, HCM, and Customer  Experience. We also have Oracle Modern Best Practices for specific industries. 04:25 Nikita: What are the key benefits of OMBP? Mitchell: Revolutionary new technologies are available for organizations and business leaders. You might wonder how existing business processes are optimized with old technology and how they can drive the best solution. With more emerging technologies reaching commercial availability, existing best practices become outdated. And to stay competitive, organizations need to continuously innovate and incorporate new technology within their best practices. In Oracle's definition of OMBPs, common business processes are considered historic input, but we also factor in what could be done with new technologies. And based on this approach, Oracle Modern Best Practices help us evolve with the organizational needs as market dynamics change, work end to end across organizations to eliminate department silos and ensure agility. It allows us to use technologies such as AI to automate the mundane and unlock human creativity for new value and insight. This allows us to incorporate next generation digital technologies to enable radically superior, measurable results. To achieve these, Oracle makes use of key differentiators such as analytics and AI and machine learning. Analytics are also known as business intelligence provides you with information in the form of pre-built dashboards, showing your key metrics in real time. Embedded analytic capabilities enable you to monitor business performance and make better decisions. 05:44 Lois: And what about AI and machine learning? Mitchell: These focus on building systems that learn or improve performance based on the data that they consume. Smart digital assistants, recommendation engines, predictive analytics, they're all used within AI and machine learning to help organizations automate operations and drive innovation, and ultimately make better decisions faster. 06:02 Nikita: Mitchell, let’s move on to the Starter Configuration. Can you explain what it is and how it helps during a cloud implementation? Mitchell: Starter Configuration is a predefined configuration of Oracle Cloud Applications aligned with the Oracle Modern Best Practices. It's very comprehensive and includes business processes in several domains, such as ERP, HCM, Supply Chain, EPM, and so on. It includes sample, master, and transactional data, and predetermined usernames, which aligns and tests based on the same use cases you saw in Oracle Modern Best Practices in Cloud Success Navigator. Customers can request deployment of a Starter Configuration into their test environment. Oracle will run an automated process for replicating the configuration, master data, transaction data, and predetermined usernames from Oracle to the Oracle Cloud Applications Test Environment of the customer's choice. For best user experience, customers can add a basic level of personalization, such as their customer name, limited number of employees, suppliers, customers, and a few other items. Starter Configuration’s delivered with predetermined step guides for comprehensive set of use cases. Using these, customers can relay the same use cases they've seen in Oracle Modern Best Practices and Success Navigator. In the Oracle Cloud Applications Test Environment Customer, we've been able to enable an in-app guidance using Oracle Guided Learning. This helps to make it easier for navigation through the business processes supported by the application. Oracle can deploy the Starter Configuration in days, not weeks or months, which means the implementation partners don't need to invest time and effort for the first configuration of an Oracle Cloud Application environment before they can even get the chance to show it to a customer. In turn, once Starter Configuration is deployed, it's ready to be used for solution familiarization and design activities. Using Starter Configuration of Oracle Cloud Applications early in the cloud journey will offer several benefits to customers. 08:00 Lois: What are these benefits? Mitchell: The first, it helps to cut down on environment configuration time from several weeks or months to potentially just days. Next, implementation partners can engage stakeholders early, and get them familiar with Oracle Cloud Applications, especially those that maybe have never participated in the sales cycle. Because customer stakeholders actually see what Oracle Cloud solutions might look like in the future, it becomes easier to take design decisions. Starte

In this episode of the Oracle University Podcast, Lois Houston and Nikita Abraham are joined by Mitchell Flinn, VP of Program Management for the CSS Platform, to explore Oracle Cloud Success Navigator.   This interactive platform is designed to help customers optimize their cloud journey, offering best practices, AI tools, and personalized guidance from implementation to innovation. Don’t miss this insider look at maximizing your Oracle Cloud investment!   Oracle Cloud Success Navigator Essentials: https://mylearn.oracle.com/ou/course/oracle-cloud-success-navigator-essentials/147489/242186 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ---------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and joining me is my co-host Lois Houston, Director of Innovation Programs.  Lois: Hi everyone! Today is the first of a two-part special on Oracle Cloud Success Navigator. This is a tool that provides you with a clear path to cloud transformation and helps you get the most out of your cloud investment. 00:52 Nikita: And to tell us more about this, we have Mitchell Flinn joining us today. Mitchell is VP of Program Management for Oracle Cloud Success Navigator. In this episode, we’ll ask Mitchell about the ins and outs of this powerful platform, its benefits, key features, and the role it plays in streamlining cloud journeys. Lois: Yeah. Hi Mitchell! What is Oracle's approach to cloud technology and customer success, and how does the Cloud Success Navigator support this philosophy? 01:22 Mitchell: Oracle has an amazing amount of industry-leading enterprise cloud technologies across our entire portfolio. All of this is at your disposal. That, coupled with the sole focus of your success, forms the crux of the company's transformational journey. In other words, we put your success at the heart of everything we do. For each organization, the path to achieve maximum value from our technology is unique. Success Navigator reflects our emphasis on being there with you throughout the entire journey to steer you to success.  01:53 Nikita: Ok, what about from a business’s viewpoint? Why would they need the Navigator? Mitchell: Businesses across every industry are moving mission-critical applications to the cloud. However, business leaders understand that there's no one-size-fits-all model for cloud development and deployment. Some fundamentals for success are your need to ensure new technologies are seamlessly integrated into day-to-day operations and continually optimize to align with evolving business requirements. You must ensure stakeholder visibility through the journey with updates at every stage. Building system efficiencies into other key tasks, which has to be done at the forefront when considering your cloud transformation. You also need to quickly identify risks and address them during the implementation process and beyond. Beyond the technical execution, cloud deployments also require significant process and organizational changes to ensure that adoption is aligned with business goals and delivers tangible benefits. Moreover, the training process for new features after cloud adoption can be an organization wide initiative that needs special attention. These requirements or more can be addressed through Oracle Cloud Success Navigator, which is a new interactive digital platform to guide you through all stages of your cloud journey. 03:09 Lois: Mitchell, how does Cloud Success Navigator platform enhance the user experience? How does it support customers at different stages of their cloud journey? Mitchell: Platform is included for free for all cloud application customers. And core to Success Navigator is the goal of increasing transparency among customers, partners in the Oracle team, from project kickoff through quarterly releases. Included in the platform are implementation best practices, Oracle Modern Best Practices focused on solutions provided by our applications, and guidance on living within the cloud.   Success Navigator supports you for every stage of your Oracle journey. You can first get your bearings and understand what's possible with your cloud solution using preconfigured starter environments to support your design decisions. It helps you chart a proven course by providing access to Oracle expertise and Oracle Modern Best Practices, so you can use cloud quality standards to guide your implementation approach. You can find value from quarterly releases using AI assistants and preview environments to experience and adopt latest features that matter to you. And you can blaze new trails by building your own cloud roadmap based on your organization's goals, keeping you focused on the capabilities you need for day-to-day and the road ahead. 04:24 Nikita: How does the Navigator cater to the needs of all the different customers? Mitchell: For customers just getting started with Oracle implementations, Navigator provides a framework with success criteria for each stakeholder involved in the implementation, and provides recommended milestones and checklists to keep everyone on track. For existing customers and experienced cloud customers thriving in the cloud, it provides contextually relevant insights based on your cloud landscape. It prepares you for quarterly releases and preview environments, and enables the use of AI and optimization within your cloud investment. For our partners, it allows Oracle to work in a collaborative way to really team up for our customers. Navigator gives transparency to all stakeholders and helps determine what success criteria we should be thinking about at each milestone phase of the journey. And it also helps customers and partners get more out of their Oracle investment through a seamless process. 05:20 Lois: Right. Mitchell, can you elaborate on the use cases of the platform? How does it address challenges and requirements during cloud implementations? Mitchell: We can create transparency and alignment between you, your partner, and the Oracle team using shared view of progress measured through standard criteria. We can incorporate recommended key milestones and activities to help you visualize and measure your progress. And we can use built-in assessments, remove risk, and ask the right questions at the right time to make the right implementation decisions for your organization. Additionally, we can use Starter Configuration, which allows you to experience the latest capabilities and leading practices to enrich design decisions for your organization with Starter Configuration. This can activate Starter Configuration early in your journey to understand what delivered capability can do for you. It allows you to evaluate modern best practices to determine how your design process can work in the future. And it empowers and educates your organization by interacting with real capability, using real processes to make the right decisions for your cloud implementation. You're able to access new features in Fusion updates. You can do this to learn what you need to know about new features in a one-stop shop and connect your company in a compelling capacity. You can find, familiarize, and prioritize new and existing features in one place. And you can experience new features in hands-on preview environments available with you with each quarterly release. You can explore new theme-based approaches using adoption centers for AI and Redwood to understand where to start and how to get there. And you can understand innovation opportunities based on business processes, data insights, and industry benchmarks. 07:01 Nikita: Now that we’ve covered the basics, can you walk us through some of the key features of the platform? Let’s start with the Home page. Mitchell: This is the starting point of the customer journey and the central location for everything Navigator has to offer, including best practice content. You'll find content focused on implementation phase, the innovation phase, and administrative elements like the team structure, program and projects, and other relevant tips and tricks. Cloud Quality Standards provides learning content and checklists for successful business transformation. This helps support the effective adoption and adherence to Cloud Quality Standards and enables individuals to leverage AI and predictive insights. The feature Sunburst allows capability for features to be reviewed in an interactive graphic, illustrating new features by pillar, other attributes, which enable customers to review features curated to identify and adopt new features that meet their needs. It helps you understand recommended features across your application base based off of a production profile, covering mandatory adoption requirements, efficiency gains, innovation capabilities like AI and Redwood to drive business change. Next is the Adoption Center, which addresses the need of our existing and implementing customers. It covers the concept of how Redwood is an imperative for our application customers, what it means, and how, and when we could translate some of the requirements to a business user or an IT user. Roadmap is an opportunity for the team to evaluate which features are most interesting at any given moment, the items that they would like to adopt next, and save features or items that they might require later. 08:36 Lois: That’s great. Mitchell, I know

In the final episode of this series on Oracle GoldenGate 23ai, Lois Houston and Nikita Abraham welcome back Nick Wagner, Senior Director of Product Management for GoldenGate, to discuss how parameters shape data replication. This episode covers parameter files, data selection, filtering, and transformation, providing essential insights for managing GoldenGate deployments.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------------------------------- Podcast Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! This is the last episode in our Oracle GoldenGate 23ai series. Previously, we looked at how you can manage Extract Trails and Files. If you missed that episode, do go back and give it a listen.  00:50 Lois: Today, Nick Wagner, Senior Director of Product Management for GoldenGate, is back on the podcast to tell us about parameters, data selection, filtering, and transformation. These are key components of GoldenGate because they allow us to control what data is replicated, how it's transformed, and where it's sent. Hi Nick! Thanks for joining us again. So, what are the different types of parameter files? Nick: We have a GLOBALS parameter file and your runtime parameter files. The global one is going to affect all processes within a deployment. It's going to be things like where's your checkpoint table located in name, things like the heartbeat table. You want to have a single one of these across your entire deployment, so it makes sense to keep it within a single file. We also have runtime parameter files. This are going to be associated with a specific extract or replicat process. These files are located in your OGG_ETC_HOME/conf/ogg. The GLOBALS file is just simply named GLOBALS and all capitals, and your parameter file names for the processes themselves are named with the process.prm. So if my extract process is EXT demo, my parameter file name will be extdemo.prm. When you make changes to parameter files, they don't take effect until the process is restarted. So in the case of a GLOBALS parameter file, you need to restart the administration service. And in a runtime parameter file, you need to restart that specific process before any changes will take effect. We also have what we call a managed process setting profile. And this allows you to set up auto restart profiles for each process. And the GoldenGate Gate classic architecture, this was contained within the GLOBALS parameter file and handled by the manager. And microservices is a little bit different, it's handled by the service manager itself. But now we actually set up profiles. 02:41 Nikita: Ok, so what can you tell us about the extract parameter file specifically?  Nick: There's a couple things within the extract parameter file is common use. First, we want to tell what the group name is. So in this case, it would be our extract name. We need to put in information on where the extract process is going to be writing the data it captures to and that would be our trail files, and extract process can write to one or more trail files. We also want to list out the list of tables and schemas that we're going to be capturing, as well as any kind of DDL changes. If we're doing an initial load, we want to set up the SQL predicate to determine which tables are being captured and put a WHERE clause on those to speed up performance. We can also do filtering within the extract process as well. So we write just the information that we need to the trail file. 03:27 Nikita: And what are the common parameters within an extract process? Nick: There are a couple of common parameters within your extract process. We have table to list out the list of tables that GoldenGate is going to be capturing from. These can be wildcarded. So I can simply do table.star and GoldenGate will capture all the tables in that database. I can also do schema.star and it will capture all the tables within a schema. We have our EXTTRAIL command, which tells GoldenGate which trail to write to. If I want to filter out certain rows and columns, I can use the filter cols and cols except parameter. GoldenGate can also capture sequence changes. So we would use the sequence parameter. And then we can also set some high-level database options for GoldenGate that affect all the tables and that's configured using the tranlog options parameter.  04:14 Lois: Nick, can you talk a bit about the different types of tranlogoptions settings? How can they be used to control what the extract process does? Nick: So one of the first ones is ExcludeTag. So GoldenGate has the ability to exclude tagged transactions. Within the database itself, you can actually specify a transaction to be tagged using a DBMS set tag option. GoldenGate replicat also sets its transactions with a tag so that the GoldenGate process knows which transactions were done by the replicat and it can exclude them automatically. You can do exclude tag with a plus. That simply means to exclude any transaction that's been tagged with any value. You can also exclude specific tags.  Another good option for TranLogOptions is enable procedural replication. This allows GoldenGate to actually capture and replicate database procedure calls, and this would be things like DBMS AQ, NQ operations, or DQ operations. So if you're using Oracle advanced queuing and you need GoldenGate to replicate those changes, it can.  Another valuable tranlogoption setting is enable auto capture. Within the Oracle Database, you can actually set ALTER TABLE command that says ALTER TABLE, enable logical replication. Or when you create a table, you can actually do CREATE TABLE statement and at the end use the enable logical replication option for that CREATE TABLE statement. And this tells GoldenGate to automatically capture that table. One of the nice features about this is that I don't need to specify that table and my parameter file, and it'll automatically enable supplemental logging on that table for me using scheduling columns. So it makes it very easy to set up replication between Oracle databases.  06:01 Nikita: Can you tell us about replicat parameters, Nick? Nick: Within a replicat, we'll have the group name, some common other parameters that we'll use is a mapping parameter that allows us to map the source to target table relationships. We can do transformation within the replicat, as well as error handling and controlling group operations to improve performance. Some common replicat parameters include the replicat parameter itself, which tells us what the name of that replicat is. We have our map statement, which allows us to map a source object to a target object. We have things like rep error that control how to handle errors. Insert all records allows us to change and convert, update, and delete operations into inserts. We can do things like compare calls, which helps with active-active replication in determining which columns are used in the GoldenGate WHERE clause. We also have the ability to use macros and column mapping to do additional transformation and make the parameter file look elegant. 07:07 AI is being used in nearly every industry…healthcare, manufacturing, retail, customer service, transportation, agriculture, you name it! And it’s only going to get more prevalent and transformational in the future. It’s no wonder that AI skills are the most sought-after by employers. If you’re ready to dive in to AI, check out the OCI AI Foundations training and certification that’s available for free! It’s the perfect starting point to build your AI knowledge. So, get going! Head on over to mylearn.oracle.com to find out more. 07:47 Nikita: Welcome back! Let’s move on to some of the most interesting topics within GoldenGate… data mapping, selection, and transformation. As I understand, users can do pretty cool things with GoldenGate. So Nick, let’s start with how GoldenGate can manipulate, change, and map data between two different databases. Nick: The map statement within a Replicat parameter allows you to provide specifications on how you're going to map source and target objects. You can also use a map and an extract, but it's pretty rare. And that would be used if you needed to write the object name. Inside the trail files is a different name than the actual object name that you're capturing from. GoldenGate can also do different data selection, mapping, and manipulation, and this is all controlled within the Extract and Replicat parameter files. In the classic architecture of GoldenGate, you could do a rudimentary level of transformation and filtering within the extract pump. Now, the distribution service is only allowing you to do filtering. Any transformation that you had within the pump would need to be moved to the Extract or the Replicat process.  The other thing that you can do within GoldenGate is select and filter data based on different levels and conditions. So within your parameter clause, you have your Table and Map statement. That's the core of everything. You have your filtering. You have COLS and COLSEXCEPT, which allow you to determine which columns you're going to include or exclude from replication. The Table and Map stat

In this episode of the Oracle University Podcast, Lois Houston and Nikita Abraham explore the intricacies of trail files in Oracle GoldenGate 23ai with Nick Wagner, Senior Director of Product Management.   They delve into how trail files store committed operations, preserving the order of transactions and capturing essential metadata. Nick explains that trail files are self-describing, containing database and table definition records, making them easier to work with. The episode also covers trail file management, including the purge trail task and the ability to download trail files directly from the web UI, providing flexibility in various deployment scenarios.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------------- Podcast Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome back to another episode of the Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and I’m joined by Lois Houston, Director of Innovation Programs. Lois: Hi there! In our last episode, we discussed the Replicat process. That was a good introduction, and you should give it a listen if you’re interested in the fundamentals of GoldenGate 23ai.  00:49 Nikita: Nick Wagner, Senior Director of Product Management for Oracle GoldenGate, is back with us today to talk about how to manage Extract Trails and Files. Hi Nick, it’s a pleasure to have you with us. So, we’ve spoken about trail files in our earlier episodes. But can you tell us about the kind of information that’s actually stored in these files?  Nick: The trail files contain committed operations only. In an Oracle environment, the extract process is actually able to understand and read both committed and uncommitted transactions. It holds the uncommitted activity and the cache manager associated settings. As a transaction is committed, it's then flushing that information to the trail file. All this information in the transaction is preserved, so we have not only the transaction itself, but the order of the operations within that transaction. All the changed columns, including the primary key and any scheduling columns are also captured, and this is controlled by the log or sub calls parameter and other parameters within the extract process. The data captured depends on settings in the extract file and you can include additional information, including tokens. The trail files also contain metadata information, where the trail files are what we call self-describing, which means that as we start reading in new objects, we start writing the definition of those objects into the trail file themselves. 02:11 Lois: Nick, what does the structure of a trail file look like? Nick: The trail files have a header information, which simply keeps information about what version of trail file this is, where GoldenGate is handling it, information about that trail file itself. You'll also have three different types of records. You'll have a data record, which contains the actual before and after images, the table update statement, the type of operations. You have a database definition record, which includes information about the database that GoldenGate is capturing from, and then you'll also have a table definition record. As GoldenGate starts up and creates a trail file for the first time, it's always going to write the trail file header and associated database definition record, and then it's going to start reading data out of the source database. As it encounters a new table for the first time in that trail file, it's going to write the metadata for that object as well. This makes it very easy. This means that within a single trail file, any data records I have in there, that trail file also contains the associated table definition record for that table. 03:20 Nikita: Let’s talk about compatibility between different versions of GoldenGate. How do the trail files fit into that? Nick: The GoldenGate trail files themselves have information built into them to help understand what they're compatible with as far as GoldenGate releases. If I'm replicating from a new version of GoldenGate to an older version of GoldenGate, I can set the format release value to tell the extract process to write these trail files in an older version. In this case, I can simply say format release 19 and it'll write the trail files in the 19C version. If you're going from an older version to a newer version of GoldenGate, it's automatically able to process the old version trail file structure without having to change anything.  04:02 Nikita: Now, GoldenGate is constantly generating these trail files as it runs. So, how do we manage them over time. What’s the cleanup process like? Nick: Within the GoldenGate microservices architecture, the web UI has a way to manage your trail files and clean them up. So there's a purge trail task that allows you to go in and set up rules on how long to keep the trail files around for before they're purged. We have customers that want to reposition extract and so you'll want to make sure that you keep trail files around long enough so that you can handle any reposition that you intend to do. Trail files will always be kept around even past their purge rules if they're still needed for GoldenGate recovery. Also new to GoldenGate 23ai is the ability to download trail files directly from the web UI. This is extremely helpful if you're using OCI GoldenGate or you don't have OS access on the machine where GoldenGate is running. 04:56 Lois: What if we want to look inside these trail files and actually see the individual records? How can we examine them directly? Nick: Well, that can be seen using a tool called Logdump. Logdumps utility, that's installed in your ogghome/bindirectory. It has online help as well as full documentation. 05:14 Lois: And how do you use Logdump? Nick: So to use Logdump, the first thing you'll do is launch the service and then you'll open a trail file. You would specify the full path of the trail file along with the path name and the sequence number of that trail file. Once you've set it up, you'll position into that location within that trail file. Normally people position at record 0 and then they'll do a next, which allows them to get the next information. There's a couple other commands in there, such as POS, which allows you to set the position, scan for header, allows you to scan to the next record if you position within the middle of a record. So, when you first run Logdump, it's not going to have very much information available for you. So, you'll want to turn on a couple of settings. You'll want to enable File Header, GHDR, and Detail to be able to see more information about what's going on within that record within the trail. Logdump also has the ability to show you the actual ASCII values as opposed to the text value. This is very useful for dealing with multibyte data as well as unprintable characters. You can also specify the length of the record to show for each Logdump record. And this is in the reclen parameter, 280 is a rough number and it will usually show about enough that'll fit on a single page. 06:40 Join the Oracle University Learning Community and tap into a vibrant network of over 1 million members, including Oracle experts and fellow learners. This dynamic community is the perfect place to grow your skills, connect with likeminded learners, and celebrate your successes. As a MyLearn subscriber, you have access to engage with your fellow learners and participate in activities in the community. Visit community.oracle.com/ou to check things out today! 07:12 Nikita: Welcome back! Nick, earlier you mentioned data records in trail files. What kind of information do these records contain? Nick: When we start looking at data records within the trail file, we're going to see a little bit different format. It's going to give us information about what type of operation this was, the before, after indicator, is this an after image or a before image? It's going to give us the time information. It's going to tell us what table this record was on and the values within that record. We can also count the number of records in a trail using the count option that tells us how many records in the trail, the average size, and then the operation type breakdown. We can also get some additional details on that count, including having it broken out by table and operation within those tables. This is really useful if you're trying to track down a missing record or an out of sync condition and you want to make sure that GoldenGate is appropriately capturing all the changes. We can also use an option within Logdump called scan for metadata. The shorthand for this command is sfmd, it allows you to scan for something like a database definition record.  You may have multiple database definition records versions within the same trail file. It tells us what type of database this was, the character set, which is important because this information is used by the replica when it goes to apply changes into the target database. We can also scan for metadata to get table definition records. The data types are numeric values that are associated with an internal GoldenGate data type. 08:43 Lois: Thank you, Nick, for your insights. There’s a lot more you can find in the Oracle GoldenGate 23ai: Fundamentals c

In this episode, Lois Houston and Nikita Abraham, along with Nick Wagner, Senior Director of Product Management, dive into the Replicat process in Oracle GoldenGate 23ai.   They discuss how Replicat applies changes to the target database, highlighting the different types: Classic, Coordinated, and Parallel Replicat.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ---------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to another episode of the Oracle University Podcast. I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! If you’ve been listening to us these last few weeks, you’ll know we’ve been discussing the fundamentals of GoldenGate 23ai. Today is going to be all about the Replicat process. Again, this is something we’ve discussed briefly in earlier episodes, but just to recap, the Replicat process applies changes from the source database to the target database. It's responsible for reading trail files and applying the changes to the target system. 01:04 Lois: That’s right, Niki. And we’ll be chatting with Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Thanks for joining us again today. Let’s get straight into it. Can you give us an overview of the Replicat process? Nick: One thing that's very important is the Replicat is extremely chatty with that target database. So it's going to be going in and trying to make lots of little transactions on that system. The Replicat process only issues single row DML. So if you can imagine a source database that's generating hundreds of thousands of changes per second, we're going to have to have a Replicat process that can do 100,000 changes per second on that target site. That means that it's going to have to send a lot of little one record commands. And so we've got a lot of ways to optimize that. But in all situations you're really going to want very, very low ping time between that Replicat process and that target database. This often means that if you're going to be running GoldenGate in a cloud, you're going to want the Cloud GoldenGate environment to be running in that target data center, wherever that target database is. 02:06 Lois: What are the key characteristics of the process, Nick? Nick: Replicat process is going to read the changes from the trail file and then apply them to the target system, just like any database user would. It's not doing anything special where it's going under the covers and trying to apply directly to the database blocks. It's just applying regular standard insert, update, delete, and DDL statements to that target database. A single trail file does support high volume of data replication activity depending on the type of Replicat. Replicats do preserve the boundary of their transactions. So in the situations, by default, a transaction that's on the source, let's say five inserts followed by a commit will remain five inserts followed by a commit on the target site. There are some operations and changes that do affect this, but they're not turned on by default. There are things like group transactions that allows you to group multiple transactions into a single commit. This one could actually improve performance in some cases. We also have batch SQL that can change the boundaries of a transaction as well. And then in a Parallel Replicat, you actually have the ability to split a large transaction into multiple chunks and apply those chunks in Parallel. So again, by default, it's going to preserve the boundaries, but there are ways to change that. And then the Replicats use a checkpoint table to help with recovery and to know where they're applying data and what they've done. The other thing in here is, like an Extract process can write to multiple trails and write subsets of data to each one, a Replicat can only process a single set of trail files at once. So it's going to be attached to a specific trail file like trail file AB, and will only be able to read changes from trail file AB. If I have multiple trails that need to be applied into a target system, then I have to set up multiple Replicats to handle that. 03:54 Nikita: So, what are the different Replicat types, Nick? Nick: We have three types in the product today. We have Classic Replicat, which should really only be used for testing purposes or in environments that don't support any of the other specialized Replicats. We have Coordinated Replicat, which is a high speed apply mechanism to apply data into a target system. It does have some parallelism in it, but it's user defined parallelism. And then we have our flagship and that's Parallel Replicat. And this is the most performant lowest latency Replicat that we have. 04:25 Lois: Ok. Let’s dive a little deeper into each of them, starting with the Classic Replicat. How does it work? Nick: It's pretty straightforward. You're going to have a process that reads the trail files, and then in a single threaded fashion it's going to take the trail file logical change record, convert it to an insert, update, or delete, and then apply it into that target database. Each transaction that it does is preceded by a change to the checkpoint table. So when the transaction that the Replicat is currently doing is committed, that checkpoint table update also gets committed. That way when the Replicat restarts, it knows exactly what transaction it left off and how it last applied the record. And all the Replicats work the same way with regards to checkpoint tables. They each have their own little method of ensuring that the transaction they're applying is also reflected within the checkpoint table so that when it restarts, it knows exactly where it happened. That way, if a Replicat dies in the middle of a transaction, it can be restarted without any duplicate data or without missing data. 05:29 Did you know that Oracle University offers free courses on Oracle Cloud Infrastructure? You’ll find training on everything from multicloud, database, networking, and security to artificial intelligence and machine learning, all free for our subscribers. So, what are you waiting for? Pick a topic, head over to mylearn.oracle.com, and get started. 05:53 Nikita: Welcome back! Moving on, what about Coordinated Replicat? Nick: The Coordinated Replicat is going to read from a set of trail files. It's going to have multiple threads that do this. So you have your base thread, your coordinated thread that's going to be thread 1. It's going to process the data and apply it into that target database. You then have thread 2, 4, 5, 6, and so on. When you set up your Replicat parameter file for a Coordinated Replicat, the map commands that maps from one table on the source to a table on the target has an additional option. So you'll have an option called a range or thread range. With the range and thread range option, you can actually tell which table to go into which thread. 06:38 Lois: Can you give us an example of this? Nick: So I could say map Scott.M into thread 1 and I want Scott.Dept into thread 2. Well, this is fantastic until you realize that Scott.M and Scott.Dept have a foreign key between them or a child dependencies, parent-child relationships. What that means is that now I'm going to have to disable that foreign key on the target site, because there's no way for GoldenGate to coordinate the changes in one thread to another thread. And so you really have to be careful on how you pair your tables together. If you don't have any referential integrity on that target database, then you can use parallel coordinated Replicat to really high degrees of parallelism, and you get some very good performance out of it. Let's say that you have a table that's really got too much data for even a single thread to process, that's where the thread range comes in. And thread range command will use something like the table's primary key to split transactions on that table across multiple threads. So I can say, hey, take my table Scott.M and I want to spread transactions across threads 10, 11, 12, 13, and 14 and then spread them evenly based on the primary key. And Coordinated Replicat will do that. So you can get some very high performance numbers out of it and you can really fine tune the tables, especially if you know the amount of data coming into each one. While this does work great, we observed that a lot of customers really don't know their applications to that level of detail, and so we needed a different method to push data into that target database, where we could define the parallelism based on the database expectations. So instead of the customer having to try and figure out what are the parent-child relationships, why can't GoldenGate do it for me? And that led to Parallel Replicat.  08:26 Nikita: And what are the benefits and features of the Parallel Replicat process?  Nick: So Parallel Replicat has been around for quite a few years now. It supports most targets, it was Oracle initially, but now it's been expanded out to a lot of the non-Oracle targets and even some of the nonrelational database targets. It has absolutely the best performance of any Replicat process out there. You can use it to split large transactions as well. So if all of a sudden you have a bat

In this episode, Lois Houston and Nikita Abraham dive into key components of Oracle GoldenGate 23ai with expert insights from Nick Wagner, Senior Director of Product Management.   They break down the Distribution Service, explaining how it moves trail files between environments, replaces the classic extract pump, and ensures secure data transfer. Nick also introduces Target Initiated Paths, a method for connecting less secure environments to more secure ones, and discusses how the Receiver Service simplifies monitoring and management. The episode wraps up with a look into Initial Load, covering different methods for syncing source and target databases without downtime.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs.  Lois: Hey there! Last week, we spoke about the Extract process and today we’re going to spend time discussing the Distribution Path, Target Initiated Path, Receiver Server, and Initial Load. These are all critical components of the GoldenGate architecture, and understanding how they work together is essential for successful data replication. 00:58 Nikita: To help us navigate these topics, we’ve got Nick Wagner joining us again. Nick is a Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Thanks for being with us today. To kick things off, can you tell us what the distribution service is and how it works? Nick: A distribution path is used when we need to send trail files between two different GoldenGate environments. The distribution service replaces the extract pump that was used in GoldenGate classic architecture. And so the distribution service will send the trail files as they're being created to that receiver service and it will write the trail files over on the target system. The distribution service works in a kind of a streaming fashion, so it's constantly pulling the trail files that the extract is creating to see if there's any new data. As soon as it sees new data, it'll packet it up and send it across the network to the receiver service. It can use a couple of different methods to do this. The most secure and recommended method is using a WebSocket secure connection or WSS. If you're going between a microservices and a classic architecture, you can actually tell the distribution service to send it using the classic architecture method. In that case, it's the OGG option when you're configuring the distribution service. There's also some unsecured methods that would send the trail files in plain text. The receiver service is then responsible for taking that data and rewriting it into the trail file on the target site. 02:23 Lois: Nick, what are some of the key features and responsibilities of the distribution service? Nick: It's responsible for command deployment. So any time that you're going to actually make a command to the distribution service, it gets handled there directly. It can handle multiple commands concurrently. It's going to dispatch trail files to one or more receiver servers so you can actually have a single distribution path, send trail files to multiple targets. It can provide some lightweight filtering so you can decide which tables get sent to the target system. And it also is integrated in with our data streams, our pub and subscribe model that we've added in GoldenGate 23ai. 03:01 Lois: Interesting. And are there any protocols to remember when using the distribution service? Nick: We always recommend a secure WebSocket. You also have proxy support for use within cloud environments. And then if you're going to a classic architecture GoldenGate, you would use the Oracle GoldenGate protocol. So in order to communicate with the distribution service and send it commands, you can communicate directly from any web browser, client software-- installation is not required-- or you can also do it through the admin client if necessary, but you can do it directly through browsers. 03:33 Nikita: Ok, let's move on to the target initiated path. Nick, what is it and what does it do essentially? Nick: This is used when you're communicating from a less secure environment to a more secure environment. Often, this requires going through some sort of DMZ. In these situations, a connection cannot be established from the less secure environment into the more secure environment. It actually needs to be established from the more secure environment out. And so if we need to replicate data into a more secure environment, we need to actually have the target GoldenGate environment initiate that connection so that it can be established.  And that's what a target-initiated path does. 04:12 Lois: And how do you set it up? Nick: It's pretty straightforward to set up. You actually don't even need to worry about it on the source side. You actually set it up and configure it from the target. The receiver service is responsible for receiving the trail file data and writing it to the local trail file. In this situation, we have a target-initiated path created. And so that receiver service is going to write the trail files locally and the replicat is going to apply that data into that target system. 04:37 Nikita: I also want to ask you about the Receiver service. What is it really? Nick: Receiver service is pretty straightforward. It's a centrally controlled service. It allows you to view the status of your distribution path and replaces target side collectors that were available in the classic architecture of GoldenGate. You can also get statistics about the receiver service directly from the web UI.  You can get detailed information about these paths by going into the receiver service and identifying information like network details, transfer protocols, how many bytes it's received, how many bytes it's sent out. If you need to issue commands from the admin client to the receiver service, you can use the info command to get details about it. Info all will tell you everything that's running. And you can see that your receiver service is up and running. 05:28 Are you working towards an Oracle Certification this year? Join us at one of our certification prep live events in the Oracle University Learning Community. Get insider tips from seasoned experts and learn from others who have already taken their certifications. Go to community.oracle.com/ou to jump-start your journey towards certification today! 05:53 Nikita: Welcome back. In the last section of today’s episode, we’ll cover what Initial Load is. Nick, can you break down the basics for us? Nick: So, the initial load is really used when you need to synchronize the source and target systems. Because GoldenGate is designed for 24/7 environments, we need to be able to do that initial load without taking downtime on the source. And so all the methods that we talk about do not require any downtime for that source database. 06:18 Lois: How do you do the initial load? Nick: So there's a couple of different ways to do the initial load. And it really depends on what your topology is. If I'm doing like-to-like replication in a homogeneous environment, we'll say Oracle-to-Oracle, the best options are to use something that's integrated with GoldenGate, some sort of precise instantiation method that does not require HandleCollisions. That's something like a database backup and restoring it to a specific SDN or CSN value using a Database Snapshot. Or in some cases, we can use Oracle Data Pump integration with GoldenGate. There are some less precise instantiation options, which do require HandleCollisions. We also have dissimilar initial load methods. And this is typically when you're going between heterogeneous environments. When my source and target databases don't match and there isn't any kind of fast unload or fast load utility that I could use between those two databases. In almost all cases, this does require HandleCollisions to be used. 07:16 Nikita: Got it. So, with so many options available, are there any advantages to using GoldenGate's own initial load method?  Nick: While some databases do have very good fast load and unload utilities, there are some advantages to using GoldenGate's own initial load method. One, it supports heterogeneous replication environments. So if I'm going from Postgres to Oracle, it'll do all the data type transformation, character set transformation for me. It doesn't require any downtime, if certain conditions are met.  It actually performs transformation as the data is loaded, too, as well as filtering. And so any transformation that you would be doing in your normal transaction log replication or CDC replication can also go through the same transformation for the initial load process. GoldenGate's initial load process does read directly from the source tables. And it fetches the data in arrays. It also uses parallel processing to speed up the replication. It does also handle activity on the source tables during the initial load process, so you do not need to worry about quiescing that source database. And a lot of the initial load methods directly built into GoldenGate support distributed application analytics targets, includi

The Extract process is the heart of Oracle GoldenGate 23ai, capturing data changes with precision. In this episode, Lois Houston and Nikita Abraham sit down with Nick Wagner, Senior Director of Product Management, to break down Extract’s role, architecture, and best practices.   Learn how Extract works across different setups, from running on source databases to using a Hub model for greater flexibility. Additionally, understand how trail files, parameter files, and naming conventions impact performance.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. -------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me today is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! Last week, we spoke about installing GoldenGate and today, we’re diving into the Extract process. We’ve discussed it briefly in an earlier episode, but to recap, the Extract process captures changes from the source database and writes them to a trail file. 00:54 Lois: Joining us again is Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Before we get into the Extract process, can you walk us through the different architecture options available for GoldenGate. Let’s start with when GoldenGate is installed on the same server as the source database. What are the benefits of this architecture? Nick: There's a couple of advantages to this. It means that GoldenGate can use the same resources on that source database. It means that you don't need another host to support the GoldenGate environment. It also means that GoldenGate can use a bequeathed connection to connect from the Extract process into the source database to make it run faster. The restrictions on this are that the Replicat process is highly communicative with the target database. What that really means is that the Replicat process is constantly doing lots of little transactions. And so the network latency between the Replicat process and the target database should really be around 4 milliseconds or less for optimal performance. So that means that a lot of people can't really run GoldenGate on the source system, even though it's an option, because they need that Replicat latency performance. And so they'll often install GoldenGate on the same server as the target database. In this case, they can use the Replicat to connect using a bequeath connection to that target system, you know that it's going to be highly performant and that latency is not going to be an issue. This works really well because the Extract process has actually been optimized to do remote capture. And so it's actually able to handle 80 milliseconds round trip ping time or less between the actual Extract process and the source database itself. And so a lot of customers will opt for this method, where they're actually running GoldenGate away from the target, or excuse me, away from the source database. 02:44 Nikita: Interesting. And is there an option where you don’t need to install GoldenGate on the actual source or target database? Nick: We also have another architecture pattern called a Hub model. And this is what you would see in something like OCI GoldenGate or OCI Marketplace, or even in third party clouds environments where you don't have the ability to install GoldenGate on the actual source or target database. In these cases, GoldenGate is just going to run on a virtual machine or an environment that you have set up specifically for GoldenGate. Now, this GoldenGate Hub doesn't need to have any database software installed. It doesn't need to have any database information on it. It's simply working as a client. So GoldenGate Extract process is a client connecting into the source database and the Replicat is a client connecting into the target database. And this really gives you a lot of flexibility. However, in some cases, there may be too much of a distance, so you won't be able to get both less than 80 milliseconds on the source side in less than 4 milliseconds on the round trip on the target side. And so in that case, you can have multiple GoldenGate Hubs. And so you would have a Hub on the Extract side and another Hub on the Replicat side. And all these are fully accessible. In this case, you'll actually use the distribution service to send the trail files from one system to another.  04:00 Lois: So, coming to the Extract process, what does it actually do?  Nick: The Extract process is configured to capture changes from that source database. In different terminology, it can subscribe to a topic if we're pulling data out of a Kafka queue or a topic or some messaging system like a JMS queue and relational database language, we're pulling database from the database transaction logs. There's a lot of different sources and targets. You can always use the GoldenGate Certification Matrix to determine which sources and targets are supported, and where we can extract data from. The capture process also connects to the source table for initial loads. When we do the initial load, instead of reading from the transaction logs, GoldenGate is actually going to do a select star on that table to get the information it needs for that load. 04:49 Lois: And what about the Extract process group?  Nick: The process group is kind of a grouping of the process itself, which is either going to be my Extract or Replicat and associated files. So in an Extract environment, we have our parameter file and a report file and our checkpoint files. The parameter file, the .prm file, is going to list out which objects we're going to capture and how we're going to capture that data. It also controls what we're going to be writing to the trail file and where that trail file exists. The report file is really just a log of what's going on in that Extract process, how it's working, what tables it's encountered. It's used for any troubleshooting to make sure everything is running smoothly. And then you also have the checkpoint files. The checkpoint files and report files should not be modified by the user, the parameter file can be. The checkpoint files are going to include information about where that process is reading from, where it's writing to, and any open transaction that it's tracking as part of the bounded recovery or cache manager functionality. 05:54 Nikita: How do you go about creating an Extract group? Nick: The Extract group can be created by doing an Add Extract command or through the UI. Each Extract must also have a unique name. On the Extract process side, there is an eight-character hard limit for the name itself. And so, you can’t have an Extract process called my Extract for today is called Nick. More than eight characters. 06:17 Lois: Nick, I was wondering, is there a simple way to identify what an Extract or Replicat is doing? Nick: If you need something to help identify what that Extract or Replicat is doing or the description of it, we do have a description field. So when you do the Add Extract or Add Replicat, there is a DESC field that allows you to add more details in. And this is really key because it allows you to put a lot more information that’s going to show up in all the log files at the service manager level. And any time you do an info on the service it’ll also bring up that description field so you can see what’s going on. That way, if you get an alert, a watch, you need to keep track of something you can easily identify what that process is doing and what it’s replicating for.  07:06 Adopting a multicloud strategy is a big step towards future-proofing your business and we’re here to help you navigate this complex landscape. With our suite of courses, you'll gain insights into network connectivity, security protocols, and the considerations of working across different cloud platforms. Start your journey to multicloud today by visiting mylearn.oracle.com. 07:32 Nikita: Welcome back! Before the break, we were talking about the description field, which helps identify what the Extract is doing. Nick, are there any best practices to keep in mind when naming a group? Nick: You also don't want to use any special characters when naming the group, especially you know things like slashes or dashes. You don't want to use spaces in them, just really stick to alphanumeric characters only. The group names are also case insensitive, so EDEPT, all capitalized is the same as edept lowercase. The other thing that you don't want to do and this isn't a hard restriction, it's just more of a friendly reminder is don't end your group with a numeric value. The report files themselves end in numeric values, so you'll have a report file, 0123456789, and so on. If you were to end your group name with a numeric value, then it can often be confused for a report file. And so you don't want to really do that. But otherwise you're free to call it whatever you want. 08:39 Lois: Got it. What about naming conventions? Are there any rules that apply? Nick: You can use whatever naming convention you want, but again, try and follow these best practices. No strange characters and don't end your process names with a numeric value. 08:53 Nikita: Can you explain the role of parameter and trail files in the Extract process? Nick: The

Installing Oracle GoldenGate 23ai is more than just running a setup file—it’s about preparing your system for efficient, reliable data replication. In this episode, Lois Houston and Nikita welcome back Nick Wagner to break down system requirements, storage considerations, and best practices for installing GoldenGate.   You’ll learn how to optimize disk space, manage trail files, and configure network settings to ensure a smooth installation.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Hello and welcome to Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and I’m joined by Lois Houston, Director of Innovation Programs.  Lois: Hi there! Last week, we took a close look at the security strategies of Oracle GoldenGate 23ai. In this episode, we’ll discuss all aspects of installing GoldenGate. 00:48 Nikita: That’s right, Lois. And back with us today is Nick Wagner, Senior Director of Product Management for GoldenGate at Oracle. Hi Nick! I’m going to get straight into it. What are the system requirements for a typical GoldenGate installation? Nick: As far as system requirements, we're going to split that into two sections. We've got an operating system requirements and a storage requirements. So with memory and disk, and I know that this isn't the answer you want, but the answer is that it varies. With GoldenGate, the amount of CPU usage that is required depends on the number of extracts and replicats. It also depends on the number of threads that you're going to be using for those replicats. Same thing with RAM and disk usage. That's going to vary on the transaction sizes and the number of long running transactions. 01:35 Lois: And how does the recovery process in GoldenGate impact system resources?  Nick: You've got two things that help the extract recovery. You've got the bonded recovery that will store transactions over a certain length of time to disk. It also has a cache manager setting that determines what gets written to disk as part of open transactions. It's not just the simple answer as, oh, it needs this much space. GoldenGate also needs to store trail files for the data that it's moving across. So if there's network latency, or if you expect a certain network outage, or you have certain SLAs for the target database that may not be met, you need to make sure that GoldenGate has enough room to store its trail files as it's writing them. The good news about all this is that you can track it. You can use parameters to set them. And we do have some metrics that we'll provide to you on how to size these environments. So a couple of things on the disk usage. The actual installation of GoldenGate is about 1 to 1.5 gig in size, depending on which version of GoldenGate you're going to be using and what database. The trail files themselves, they default to 500 megabytes apiece. A lot of customers keep them on disk longer than they're necessary, and so there's all sorts of purging options available in GoldenGate. But you can set up purge rules to say, hey, I want to get rid of my trail files as soon as they're not needed anymore. But you can also say, you know what? I want to keep my trail files around for x number of days, even if they're not needed. That way they can be rebuilt. I can restore from any previous point in time. 03:15 Nikita: Let’s talk a bit more about trail files. How do these files grow and what settings can users adjust to manage their storage efficiently? Nick: The trail files grow at about 30% to 35% of the generated redo log data. So if I'm generating 100 gigabytes of redo an hour, then you can expect the trail files to be anywhere from 30 to 35 gigabytes an hour of generated data. And this is if you're replicating everything. Again, GoldenGate's got so many different options. There's so many different ways to use it. In some cases, if you're going to a distributed applications and analytics environment, like a Databricks or a Snowflake, you might want to write more information to the trail file than what's necessary. Maybe I want additional information, such as when this change happened, who the user was that made that change. I can add specific token data. You can also tell GoldenGate to log additional records or additional columns to the trail file that may not have been changed. So I can always say, hey, GoldenGate, replicate and store the entire before and after image of every single row change to your trail file, even if those columns didn't change. And so there's a lot of different ways to do it there. But generally speaking, the default settings, you're looking at about 30% to 35% of the generated redo log value. System swap can fill up quickly. You do want this as a dedicated disk as well. System swap is often used for just handling of the changes, as GoldenGate flushes data from memory down to disk. These are controlled by a couple of parameters. So because GoldenGate is only writing committed activity to the trail file, the log reader inside the database is actually giving GoldenGate not only committed activity but uncommitted activity, too. And this is so it can stay very high speed and very low latency. 05:17 Lois: So, what are the parameters? Nick: There's a cache manager overall feature, and there's a cache directory. That directory controls where that data is actually stored, so you can specify the location of the uncommitted transactions. You can also specify the cache size. And there's not only memory settings here, but there's also disk settings. So you can say, hey, once a cache size exceeds a certain memory usage, then start flushing to disk, which is going to be slower. This is for systems that maybe have less memory but more high-speed disk. You can optimize these parameters as necessary. 05:53 Nikita: And how does GoldenGate adjust these parameters? Nick: For most environments, you're just going to leave them alone. They're automatically configured to look at the system memory available on that system and not use it all. And then as soon as necessary, it'll overflow to disk. There's also intelligent settings built within these parameters and within the cache manager itself that if it starts seeing a lull in activity or your traditional OLTP type responses to actually free up the memory that it has allocated. Or if it starts seeing more activity around data warehousing type things where you're doing large transactions, it'll actually hold on to memory a little bit longer. So it kinda learns as it goes through your environment and starts replicating data. 06:37 Lois: Is there anything else you think we should talk about before we move on to installing GoldenGate?  Nick: There's a couple additional things you need to think of with the network as well. So when you're deploying GoldenGate, you definitely want it to use the fastest network.  GoldenGate can also use a reverse proxy, especially important with microservices. Reverse proxy, typically we recommend Nginx. And it allows you to access any of the GoldenGate microservices using a single port.  GoldenGate also needs either host names or IP addresses to do its communication and to ensure the system is available. It does a lot of communication through TCP and IP as well as WSS. And then it also handles firewalls. So you want to make sure that the firewalls are open for ingress and egress for GoldenGate, too. There's a couple of different privileges that GoldenGate needs when you go to install it. You'll want to make sure that GoldenGate has the ability to write to the home where you're installing it. That's kind of obvious, but we need to say it anyways. There's a utility called oggca.sh. That's the GoldenGate Configuration Assistant that allows you to set up your first deployments and manage additional deployments. That needs permissions to write to the directories where you're going to be creating the new deployments. The extract process needs connection and permissions to read the transaction logs or backups. This is not important for Oracle, but for non-Oracle it is. And then we also recommend a dedicated database user for the extract and replicat connections. 08:15 Are you keen to stay ahead in today's fast-paced world? We’ve got your back! Each quarter, Oracle rolls out game-changing updates to its Fusion Cloud Applications. And to make sure you’re always in the know, we offer New Features courses that give you an insider’s look at all of the latest advancements. Don't miss out! Head over to mylearn.oracle.com to get started. 08:41 Nikita: Welcome back! So Nick, how do we get started with the installation?  Nick: So when we go to the install, the first thing you're going to do is go ahead and go to Oracle's website and download the software. Because of the way that GoldenGate works, there's only a couple moving parts. You saw the microservices. There's five or six of them. You have your extract, your replicat, your distribution service, trail files. There's not a lot of moving components. So if something does go wrong, usually it affects multiple customers. And so it's very important that when you go to install GoldenGate, you're using the most recent bundle patch. And you can find this within My Oracle Support. It's not always available directly from OTN

GoldenGate 23ai takes security seriously, and this episode unpacks everything you need to know. GoldenGate expert Nick Wagner breaks down how authentication, access roles, and encryption protect your data.   Learn how GoldenGate integrates with identity providers, secures communication, and keeps passwords out of storage. Understand how trail files work, why they only store committed data, and how recovery processes prevent data loss.   Whether you manage replication or just want to tighten security, this episode gives you the details to lock things down without slowing operations.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Welcome, everyone! This is our fourth episode on Oracle GoldenGate 23ai. Last week, we discussed the terminology, different processes and what they do, and the architecture of the product at a high level. Today, we have Nick Wagner back with us to talk about the security strategies of GoldenGate. 00:56 Lois: As you know by now, Nick is a Senior Director of Product Management for GoldenGate at Oracle. He’s played a key role as one of the product designers behind the latest version of GoldenGate. Hi Nick! Thank you for joining us again. Can you tell us how GoldenGate takes care of data security? Nick: So GoldenGate authentication and authorization is done in a couple of different ways. First, we have user credentials for GoldenGate for not only the source and target databases, but also for GoldenGate itself. We have integration with third-party identity management products, and everything that GoldenGate does can be secured. 01:32 Nikita: And we must have some access roles, right? Nick: There's four roles built into the GoldenGate product. You have your security role, administrator, operator, and user. They're all hierarchical. The most important one is the security user. This user is going to be the one that provides the administrative tasks. This user is able to actually create additional users and assign roles within the product. So do not lose this password and this user is extremely important. You probably don't want to use this security user as your everyday user. That would be your administrator. The administrator role is able to perform all administrative tasks within GoldenGate. So not only can they go in and create new extracts, create new replicats, create new distribution services, but they can also start and stop them. And that's where the operator role is and the user role. So the operator role allows you to go in and start/stop processes, but you can't create any new ones, which is kind of important. So this user would be the one that could go in and suspend activity. They could restart activity. But they can't actually add objects to replication. The user role is really a read-only role. They can come in. They can see what's going on. They can look at the log files. They can look at the alerts. They can look at all the watches and see exactly what GoldenGate is doing. But they're unable to make any changes to the product itself. 02:54 Lois: You mentioned the roles are hierarchical in nature. What does that mean? Nick: So anything that the user role does can be done by the operator. Anything that the operator and user roles can do can be done by the administrator. And anything that the user, operator, and administrator roles do can be done by the security role. 03:11 Lois: Ok. So, is there a single sign-on available for GoldenGate? Nick: We also have a password plugin for GoldenGate Connections. A lot of customers have asked for integration with whatever their single sign-on utility is, and so GoldenGate now has that with GoldenGate 23ai. So these are customer-created entities. So, we have some examples that you can use in our documentation on how to set up an identity provider or a third-party identity provider with GoldenGate. And this allows you to ensure that your corporate standards are met. As we started looking into this, as we started designing it, every single customer wanted something different. And so instead of trying to meet the needs for every customer and every possible combination of security credentials, we want you to be able to design it the way you need it. The passwords are never stored. They're only retrieved from the identity provider by the plugin itself. 04:05 Nikita: That’s a pretty important security aspect…that when it’s time to authenticate a user, we go to the identity provider. Nick: We're going to connect in and see if that password is matching. And only then do we use it. And as soon as we detect that it's matched, that password is removed. And then for the extract and replicats themselves, you can also use it for the database, data source, and data target connections, as well as for the GoldenGate users. So, it is a full-featured plugin. So, our identity provider plugin works with IAM as well as OAM. These are your standard identity manager authentication methods. The standard one is OAuth 2, as well as OIDC. And any Identity Manager that uses that is able to integrate with GoldenGate. 04:52 Lois: And how does this work? Nick: The way that it works is pretty straightforward. Once the user logs into the database, we're going to hand off authentication to the identity provider. Once the identity provider has validated that user's identity and their credentials, then it comes back to GoldenGate and says that user is able to log in to either GoldenGate or the application or the database. Once the user is logged in, we get that confirmation that's been sent out and they can continue working through GoldenGate. So, it's very straightforward on how it works. There's also a nice little UI that will help set up each additional user within those systems. All the communication is also secured as well. So any communication done through any of the GoldenGate services is encrypted using HTTPS. All the REST calls themselves are all done using HTTPS as well. All the data protection calls and all the communication across the network when we send data across a distribution service is encrypted using a secure WebSocket. And there's also trail file encryption at the operating system level for data at REST. So, this really gives you the full level of encryption for customers that need that high-end security. GoldenGate does have an option for FIPS 140-2 compliance as well. So that's even a further step for most of those customers. 06:12 Nikita: That’s impressive! Because we want to maintain the highest security standards, right? Especially when dealing with sensitive information. I now want to move on to trail files. In our last episode, we briefly spoke about how they serve as logs that record and track changes made to data. But what more can you tell us about them, Nick? Nick: There's two different processes that write to the trail files. The extract process will write to the trail file and the receiver service will write to the trail file. The extract process is going to write to the trail file as it's pulling data out of that source database. Now, the extract process is controlled by a parameter file, that says, hey, here's the exact changes that I'm going to be pulling out. Here's the tables. Here's the rows that I want. As it's pulling that data out and writing it to the trail files, it's ensuring that those trail files have enough information so that the replicat process can actually construct a SQL statement and apply that change to that target platform. And so there's a lot of ways to change what's actually stored in those trail files and how it's handled. The trail files can also be used for initial loads. So when we do the initial load through GoldenGate, we can grab and write out the data for those tables, and that excludes the change data. So initial loads is pulling the data directly from the tables themselves, whereas ongoing replication is pulling it from the transaction logs. 07:38 Lois: But do we need to worry about rollbacks? Nick: Our trail files contain committed data only and all data is sequential. So this is two important things. Because it contains committed data only, we don't need to worry about rollbacks. We also don't need to worry about position within that trail file because we know all data is sequential. And so as we're reading through the trail file, we know that anything that's written in a prior location in that trial file was committed prior to something else. And as we get into the recovery aspects of GoldenGate, this will all make a lot more sense. 08:13 Lois: Before we do that, can you tell us about the naming of trail files? Nick: The trail files as far as naming, because these do reside on the operating system, you start with a two-letter trail file abbreviation and then a nine-digit sequential value. So, you almost look at it as like an archive log from Oracle, where we have a prefix and then an affix, which is numeric. Same kind of thing. So, we have our two-letter, in this case, an ab, and then we have a nine-digit number. 08:47 Transform the way you work with Oracle Database 23ai! This cutting-edge technology brings

In this episode, Lois Houston and Nikita Abraham, along with Nick Wagner, focus on GoldenGate’s terminology and architectural evolution.   Nick defines source and target systems, which are crucial for data replication, and then moves on to explain the data extraction and replication processes.   He also talks about the new microservices architecture, which replaces the classic architecture, offering benefits like simplified management, enhanced security, and a user-friendly interface. Nick highlights how this architecture facilitates easy upgrades and provides a streamlined experience for administrators.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston: Director of Innovation Programs. Lois: Hi there! Thanks for joining us again as we make our way through Oracle GoldenGate 23ai. Last week, we discussed all the new features introduced in 23ai and today, we’ll move on to the terminology, the different processes and what they do, and the architecture of the product at a high level. 00:56 Nikita: Back with us is Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Let’s get into some of the terminology. What do we actually call stuff in GoldenGate? Nick: Within GoldenGate, we have our source systems and our target systems. The source is where we're going to be capturing data from, the targets, where we're going to be applying data into. And when we start talking about things like active-active or setting up GoldenGate for high availability, where your source can also be your target, it does become a little bit more complex. And so in some of those cases, we might refer to things as East and West, or America and Europe, or different versions of that. We also have a couple of different things within the product itself. We have what we call our Extract and our Replicat. The Extract is going to be the process that pulls the data out of the database, our capture technology. Our Replicat’s going to be the one that applies the data into the target system, or you can also look at it as a push technology. We have what we call our Distribution Path. Our Distribution Path is going to be how we're sending the data across the network. A lot of times when customers run GoldenGate, they don't have the luxury of just having a single server of GoldenGate that can pull data from one database and push data into another one. They need to set up multiple hops of that data. And so in that case, we would use what we call a Distribution Path to send that data from one system to the next. We also have what we call a Target Initiated Path. It's kind of a subset of your Distribution Path, but it allows you to communicate from a less secure environment into a more secure environment.  02:33 Lois: Nick, what about parameter names. I’ve seen them in uppercase…title case…does that matter?  Nick: GoldenGate has a lot of parameters. This is something you'll see all over the place within GoldenGate itself.  These parameters are in your Extract and Replicat parameter files during your distribution path parameter files. Parameters for GoldenGate are case insensitive.  Within your own environments, you can set it up to have lowercase, mixed case, whatever you want, but just be aware that they are case insensitive. GoldenGate doesn't care, it's just for readability. And then we also have something called trail files. Trail files is where GoldenGate stores all the data before we're able to apply it into that target system. Think about it as our queuing mechanism, and we're queuing everything outside the database so that we're not overloading those database environments. And that's some of the terminology for the product itself. We also have microservices within GoldenGate. 03:31 Nikita: And at the heart of everything is the Service Manager, right? Talk to us about what it is and what it does. Nick: The service manager is responsible for making sure that everything else is up and running. If you are familiar with GoldenGate classic architecture, this is kind of similar to a GoldenGate manager where that process was there to make sure that processes were running the trail files, or excuse me, that certain error logs were getting written out. If a process went down, the manager would restart that process. The service manager is performing a lot of those same functions. Now attached to the service manager, we have our configuration service. This is new in GoldenGate 23ai. This configuration service is going to allow you to set up GoldenGate for highly available environments. So you can build HA into GoldenGate itself using the configuration service. 04:22 Lois: And what does this configuration service do? Nick: This configuration service essentially moves the checkpoint files that used to be on disk into a database so that everything can be stored inside of a database.  Also attached to the service manager, we have the performance metric service. This is a service that is going to be gathering all the performance metrics of GoldenGate. So it's going to tell you how fast things are going, what the latencies are, how many bytes per second we're reading from, the transaction logs or writing to our trail files. How quickly a distribution path is sending data across a network. If you want to know any of your lag information, you'll get it from the performance metrics server. We also have the receiver service and the distribution service. These two work hand in hand to establish network communication between two GoldenGate environments. So on what we call our source system, we have a distribution service that's going to send the data to our target system. On the target system, a receiver service is going to receive that data and then rewrite the trail files. We also have the administration service that's responsible for authentication and authorization of the users, as well as making sure that people have access to the right information. 05:33 Nikita: Ok. Moving on the deployment, how is GoldenGate actually deployed, Nick? Nick: GoldenGate is kinda nice. So the way that the product is installed is you install the GoldenGate environment and that's what we call our service manager deployment under a specific GoldenGate home. So the software binaries themselves get installed under a home, we'll say U01/OGG23AI. Now once I've installed GoldenGate once, that's my OGG home. I can now have any number of service managers and deployments tied to that same home.  06:11 Lois: Ok, let’s work with an example to make this simpler. Let’s say I've got a service manager that's going be responsible for three different deployments: Accounting, Finance, and Sales. Nick: Each of these deployments is going to reside in its own directory. Each of these deployments is going to have its own set of microservices. And so this also means that each of these deployments can have their own set of users. So the people that access the GoldenGate accounting deployment can be different than the ones that access the sales deployment. This means with this distribution of roles that I can have somebody come in and administer the sales database, but they wouldn't have any information or any access to accounting or finance. And this is very important, it allows you to really pull that information apart and separate it. Each of these environments also has their own set of parameter files, Extract process, Replicat process, distribution services, and everything. So it's a very nice way of splitting things up, but all having them tied to the same GoldenGate home system. And this home is very important. So I can take a deployment, let's say my finance deployment, and if I want to move it to a new GoldenGate home and that GoldenGate home is a different version, like let's say that my original home is 23.4, my new GoldenGate home is 23.7, I simply stop that GoldenGate deployment. I stopped at a finance deployment. I changed its OGG home from 23.4 to 23.7. I restart the deployment, that deployment is automatically upgraded to the new environment and attached to the new system. So it makes upgrading very, very simple, very easy, very elegant. 07:53 Nikita: Ok. So, we’ve spoken about the services…some of the terminology. Let’s get into the architecture next. Nick: So when we talk about the architecture for GoldenGate, we used to have two different architectures. We had a classic architecture and a microservices architecture. Classic architecture was something that's been around since the very beginning of GoldenGate in the late '90s. We announced that, that architecture was deprecated in 19c. And Oracle deprecated means that feature is no longer going to be enhanced and it'll be patched selectively. And at some point in the future, it'll be entirely desupported. Well, GoldenGate 23ai is that future. And so in 23ai, the classic architecture is desupported, that means that it's no longer in the build at all. And so it's just microservices architecture. 08:41 Lois: Is there a tool to assist with this migration?  Nick: We do have a migration utility that will convert an old classic architecture into the new microservices architectur

In this episode, Lois Houston and Nikita Abraham continue their deep dive into Oracle GoldenGate 23ai, focusing on its evolution and the extensive features it offers. They are joined once again by Nick Wagner, who provides valuable insights into the product's journey.   Nick talks about the various iterations of Oracle GoldenGate, highlighting the significant advancements from version 12c to the latest 23ai release. The discussion then shifts to the extensive new features in 23ai, including AI-related capabilities, UI enhancements, and database function integration.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -----------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! Last week, we introduced Oracle GoldenGate and its capabilities, and also spoke about GoldenGate 23ai. In today’s episode, we’ll talk about the various iterations of Oracle GoldenGate since its inception. And we’ll also take a look at some new features and the Oracle GoldenGate product family. 00:57 Lois: And we have Nick Wagner back with us. Nick is a Senior Director of Product Management for GoldenGate at Oracle. Hi Nick! I think the last time we had an Oracle University course was when Oracle GoldenGate 12c was out. I’m sure there’s been a lot of advancements since then. Can you walk us through those? Nick: GoldenGate 12.3 introduced the microservices architecture. GoldenGate 18c introduced support for Oracle Autonomous Data Warehouse and Autonomous Transaction Processing Databases. In GoldenGate 19c, we added the ability to do cross endian remote capture for Oracle, making it easier to set up the GoldenGate OCI service to capture from environments like Solaris, Spark, and HP-UX and replicate into the Cloud. Also, GoldenGate 19c introduced a simpler process for upgrades and installation of GoldenGate where we released something called a unified build. This means that when you install GoldenGate for a particular database, you don't need to worry about the database version when you install GoldenGate. Prior to this, you would have to install a version-specific and database-specific version of GoldenGate. So this really simplified that whole process. In GoldenGate 23ai, which is where we are now, this really is a huge release.  02:16 Nikita: Yeah, we covered some of the distributed AI features and high availability environments in our last episode. But can you give us an overview of everything that’s in the 23ai release? I know there’s a lot to get into but maybe you could highlight just the major ones? Nick: Within the AI and streaming environments, we've got interoperability for database vector types, heterogeneous capture and apply as well. Again, this is not just replication between Oracle-to-Oracle vector or Postgres to Postgres vector, it is heterogeneous just like the rest of GoldenGate. The entire UI has been redesigned and optimized for high speed. And so we have a lot of customers that have dozens and dozens of extracts and replicats and processes running and it was taking a long time for the UI to refresh those and to show what's going on within those systems. So the UI has been optimized to be able to handle those environments much better. We now have the ability to call database functions directly from call map. And so when you do transformation with GoldenGate, we have about 50 or 60 built-in transformation routines for string conversion, arithmetic operation, date manipulation. But we never had the ability to directly call a database function. 03:28 Lois: And now we do? Nick: So now you can actually call that database function, database stored procedure, database package, return a value and that can be used for transformation within GoldenGate. We have integration with identity providers, being able to use token-based authentication and integrate in with things like Azure Active Directory and your other single sign-on for the GoldenGate product itself. Within Oracle 23ai, there's a number of new features. One of those cool features is something called lock-free reservation columns. So this allows you to have a row, a single row within a table and you can identify a column within that row that's like an inventory column. And you can have multiple different users and multiple different transactions all updating that column within that same exact row at that same time. So you no longer have row-level locking for these reservation columns. And it allows you to do things like shopping carts very easily. If I have 500 widgets to sell, I'm going to let any number of transactions come in and subtract from that inventory column. And then once it gets below a certain point, then I'll start enforcing that row-level locking. 04:43 Lois: That’s really cool… Nick: The one key thing that I wanted to mention here is that because of the way that the lock-free reservations work, you can have multiple transactions open on the same row. This is only supported for Oracle to Oracle. You need to have that same lock-free reservation data type and availability on that target system if GoldenGate is going to replicate into it. 05:05 Nikita: Are there any new features related to the diagnosability and observability of GoldenGate?  Nick: We've improved the AWR reports in Oracle 23ai. There's now seven sections that are specific to Oracle GoldenGate to allow you to really go in and see exactly what the GoldenGate processes are doing and how they're behaving inside the database itself. And there's a Replication Performance Advisor package inside that database, and that's been integrated into the Web UI as well. So now you can actually get information out of the replication advisor package in Oracle directly from the UI without having to log into the database and try to run any database procedures to get it. We've also added the ability to support a per-PDB Extract.  So in the past, when GoldenGate would run on a multitenant database, a multitenant database in Oracle, all the redo data from any pluggable database gets sent to that one redo stream. And so you would have to configure GoldenGate at the container or root level and it would be able to access anything at any PDB. Now, there's better security and better performance by doing what we call per-PDB Extract. And this means that for a single pluggable database, I can have an extract that runs at that database level that's going to capture information just from that pluggable database. 06:22 Lois And what about non-Oracle environments, Nick? Nick: We've also enhanced the non-Oracle environments as well. For example, in Postgres, we've added support for precise instantiation using Postgres snapshots. This eliminates the need to handle collisions when you're doing Postgres to Postgres replication and initial instantiation. On the GoldenGate for big data side, we've renamed that product more aptly to distributed applications in analytics, which is really what it does, and we've added a whole bunch of new features here too. The ability to move data into Databricks, doing Google Pub/Sub delivery. We now have support for XAG within the GoldenGate for distributed applications and analytics. What that means is that now you can follow all of our MAA best practices for GoldenGate for Oracle, but it also works for the DAA product as well, meaning that if it's running on one node of a cluster and that node fails, it'll restart itself on another node in the cluster. We've also added the ability to deliver data to Redis, Google BigQuery, stage and merge functionality for better performance into the BigQuery product. And then we've added a completely new feature, and this is something called streaming data and apps and we're calling it AsyncAPI and CloudEvent data streaming. It's a long name, but what that means is that we now have the ability to publish changes from a GoldenGate trail file out to end users. And so this allows through the Web UI or through the REST API, you can now come into GoldenGate and through the distributed applications and analytics product, actually set up a subscription to a GoldenGate trail file. And so this allows us to push data into messaging environments, or you can simply subscribe to changes and it doesn't have to be the whole trail file, it can just be a subset. You can specify exactly which tables and you can put filters on that. You can also set up your topologies as well. So, it's a really cool feature that we've added here. 08:26 Nikita: Ok, you’ve given us a lot of updates about what GoldenGate can support. But can we also get some specifics? Nick: So as far as what we have, on the Oracle Database side, there's a ton of different Oracle databases we support, including the Autonomous Databases and all the different flavors of them, your Oracle Database Appliance, your Base Database Service within OCI, your of course, Standard and Enterprise Edition, as well as all the different flavors of Exadata, are all supported with GoldenGate. This is all for capture and delivery. And this is all versions as well. GoldenGate supports Oracle 23ai and below. We also have a ton of non-Oracle databases in different Cloud stores. On an non-Orac

In a new season of the Oracle University Podcast, Lois Houston and Nikita Abraham dive into the world of Oracle GoldenGate 23ai, a cutting-edge software solution for data management. They are joined by Nick Wagner, a seasoned expert in database replication, who provides a comprehensive overview of this powerful tool.   Nick highlights GoldenGate's ability to ensure continuous operations by efficiently moving data between databases and platforms with minimal overhead. He emphasizes its role in enabling real-time analytics, enhancing data security, and reducing costs by offloading data to low-cost hardware. The discussion also covers GoldenGate's role in facilitating data sharing, improving operational efficiency, and reducing downtime during outages.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ---------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I’m Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston: Director of Innovation Programs. Lois: Hi everyone! Welcome to a new season of the podcast. This time, we’re focusing on the fundamentals of Oracle GoldenGate. Oracle GoldenGate helps organizations manage and synchronize their data across diverse systems and databases in real time.  And with the new Oracle GoldenGate 23ai release, we’ll uncover the latest innovations and features that empower businesses to make the most of their data. Nikita: Taking us through this is Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. He’s been doing database replication for about 25 years and has been focused on GoldenGate on and off for about 20 of those years.  01:18 Lois: In today’s episode, we’ll ask Nick to give us a general overview of the product, along with some use cases and benefits. Hi Nick! To start with, why do customers need GoldenGate? Nick: Well, it delivers continuous operations, being able to continuously move data from one database to another database or data platform in efficiently and a high-speed manner, and it does this with very low overhead. Almost all the GoldenGate environments use transaction logs to pull the data out of the system, so we're not creating any additional triggers or very little overhead on that source system. GoldenGate can also enable real-time analytics, being able to pull data from all these different databases and move them into your analytics system in real time can improve the value that those analytics systems provide. Being able to do real-time statistics and analysis of that data within those high-performance custom environments is really important. 02:13 Nikita: Does it offer any benefits in terms of cost?  Nick: GoldenGate can also lower IT costs. A lot of times people run these massive OLTP databases, and they are running reporting in those same systems. With GoldenGate, you can offload some of the data or all the data to a low-cost commodity hardware where you can then run the reports on that other system. So, this way, you can get back that performance on the OLTP system, while at the same time optimizing your reporting environment for those long running reports. You can improve efficiencies and reduce risks. Being able to reduce the amount of downtime during planned and unplanned outages can really make a big benefit to the overall operational efficiencies of your company.  02:54 Nikita: What about when it comes to data sharing and data security? Nick: You can also reduce barriers to data sharing. Being able to pull subsets of data, or just specific pieces of data out of a production database and move it to the team or to the group that needs that information in real time is very important. And it also protects the security of your data by only moving in the information that they need and not the entire database. It also provides extensibility and flexibility, being able to support multiple different replication topologies and architectures. 03:24 Lois: Can you tell us about some of the use cases of GoldenGate? Where does GoldenGate truly shine?  Nick: Some of the more traditional use cases of GoldenGate include use within the multicloud fabric. Within a multicloud fabric, this essentially means that GoldenGate can replicate data between on-premise environments, within cloud environments, or hybrid, cloud to on-premise, on-premise to cloud, or even within multiple clouds. So, you can move data from AWS to Azure to OCI. You can also move between the systems themselves, so you don't have to use the same database in all the different clouds. For example, if you wanted to move data from AWS Postgres into Oracle running in OCI, you can do that using Oracle GoldenGate. We also support maximum availability architectures. And so, there's a lot of different use cases here, but primarily geared around reducing your recovery point objective and recovery time objective. 04:20 Lois: Ah, reducing RPO and RTO. That must have a significant advantage for the customer, right? Nick: So, reducing your RPO and RTO allows you to take advantage of some of the benefits of GoldenGate, being able to do active-active replication, being able to set up GoldenGate for high availability, real-time failover, and it can augment your active Data Guard and Data Guard configuration. So, a lot of times GoldenGate is used within Oracle's maximum availability architecture platinum tier level of replication, which means that at that point you've got lots of different capabilities within the Oracle Database itself. But to help eke out that last little bit of high availability, you want to set up an active-active environment with GoldenGate to really get true zero RPO and RTO. GoldenGate can also be used for data offloading and data hubs. Being able to pull data from one or more source systems and move it into a data hub, or into a data warehouse for your operational reporting. This could also be your analytics environment too. 05:22 Nikita: Does GoldenGate support online migrations? Nick: In fact, a lot of companies actually get started in GoldenGate by doing a migration from one platform to another. Now, these don't even have to be something as complex as going from one database like a DB2 on-premise into an Oracle on OCI, it could even be simple migrations. A lot of times doing something like a major application or a major database version upgrade is going to take downtime on that production system. You can use GoldenGate to eliminate that downtime. So this could be going from Oracle 19c to Oracle 23ai, or going from application version 1.0 to application version 2.0, because GoldenGate can do the transformation between the different application schemas. You can use GoldenGate to migrate your database from on premise into the cloud with no downtime as well. We also support real-time analytic feeds, being able to go from multiple databases, not only those on premise, but being able to pull information from different SaaS applications inside of OCI and move it to your different analytic systems. And then, of course, we also have the ability to stream events and analytics within GoldenGate itself.  06:34 Lois: Let's move on to the various topologies supported by GoldenGate. I know GoldenGate supports many different platforms and can be used with just about any database. Nick: This first layer of topologies is what we usually consider relational database topologies. And so this would be moving data from Oracle to Oracle, Postgres to Oracle, Sybase to SQL Server, a lot of different types of databases. So the first architecture would be unidirectional. This is replicating from one source to one target. You can do this for reporting. If I wanted to offload some reports into another server, I can go ahead and do that using GoldenGate. I can replicate the entire database or just a subset of tables. I can also set up GoldenGate for bidirectional, and this is what I want to set up GoldenGate for something like high availability. So in the event that one of the servers crashes, I can almost immediately reconnect my users to the other system. And that almost immediately depends on the amount of latency that GoldenGate has at that time. So a typical latency is anywhere from 3 to 6 seconds. So after that primary system fails, I can reconnect my users to the other system in 3 to 6 seconds. And I can do that because as GoldenGate’s applying data into that target database, that target system is already open for read and write activity. GoldenGate is just another user connecting in issuing DML operations, and so it makes that failover time very low. 07:59 Nikita: Ok…If you can get it down to 3 to 6 seconds, can you bring it down to zero? Like zero failover time?   Nick: That's the next topology, which is active-active. And in this scenario, all servers are read/write all at the same time and all available for user activity. And you can do multiple topologies with this as well. You can do a mesh architecture, which is where every server talks to every other server. This works really well for 2, 3, 4, maybe even 5 environments, but when you get beyond that, having every server communicate with every other server can get a little complex. And so at that point we start looking at doing what we call a hub and spoke architecture, where we have lots of different spokes.

Discover how Oracle APEX leverages OCI AI services to build smarter, more efficient applications. Hosts Lois Houston and Nikita Abraham interview APEX experts Chaitanya Koratamaddi, Apoorva Srinivas, and Toufiq Mohammed about how key services like OCI Vision, Oracle Digital Assistant, and Document Understanding integrate with Oracle APEX.   Packed with real-world examples, this episode highlights all the ways you can enhance your APEX apps.   Oracle APEX: Empowering Low Code Apps with AI: https://mylearn.oracle.com/ou/course/oracle-apex-empowering-low-code-apps-with-ai/146047/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast. I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! Last week, we looked at how generative AI powers Oracle APEX and in today’s episode, we’re going to focus on integrating APEX with OCI AI Services. Lois: That’s right, Niki. We’re going to look at how you can use Oracle AI services like OCI Vision, Oracle Digital Assistant, Document Understanding, OCI Generative AI, and more to enhance your APEX apps. 01:03 Nikita: And to help us with it all, we’ve got three amazing experts with us, Chaitanya Koratamaddi, Director of Product Management at Oracle, and senior product managers, Apoorva Srinivas and Toufiq Mohammed. In today’s episode, we’ll go through each Oracle AI service and look at how it interacts with APEX. Apoorva, let’s start with you. Can you explain what the OCI Vision service is? Apoorva: Oracle Cloud Infrastructure Vision is a serverless multi-tenant service accessible using the console or REST APIs. You can upload images to detect and classify objects in them. With prebuilt models available, developers can quickly build image recognition into their applications without machine learning expertise. OCI Vision service provides a fully managed model infrastructure. With complete integration with OCI Data Labeling, you can build custom models easily. OCI Vision service provides pretrained models-- Image Classification, Object Detection, Face Detection, and Text Recognition. You can build custom models for Image Classification and Object Detection. 02:24 Lois: Ok. What about its use cases? How can OCI Vision make APEX apps more powerful? Apoorva: Using OCI Vision, you can make images and videos discoverable and searchable in your APEX app.  You can use OCI Vision to detect and classify objects in the images. OCI Vision also highlights the objects using a red rectangular box. This comes in handy in use cases such as detecting vehicles that have violated the rules in traffic images. You can use OCI Vision to identify visual anomalies in your data. This is a very popular use case where you can detect anomalies in cancer X-ray images to detect cancer. These are some of the most popular use cases of using OCI Vision with your APEX app. But the possibilities are endless and you can use OCI Vision for any of your image analysis. 03:29 Nikita: Let’s shift gears to Oracle Digital Assistant. Chaitanya, can you tell us what it’s all about? Chaitanya: Oracle Digital Assistant is a low-code conversational AI platform that allows businesses to build and deploy AI assistants. It provides natural language understanding, automatic speech recognition, and text-to-speech capabilities to enable human-like interactions with customers and employees. Oracle Digital Assistant comes with prebuilt templates for you to get started.  04:00 Lois: What are its key features and benefits, Chaitanya? How does it enhance the user experience? Chaitanya: Oracle Digital Assistant provides conversational AI capabilities that include generative AI features, natural language understanding and ML, AI-powered voice, and analytics and insights. Integration with enterprise applications become easier with unified conversational experience, prebuilt chatbots for Oracle Cloud applications, and chatbot architecture frameworks. Oracle Digital Assistant provides advanced conversational design tools, conversational designer, dialogue and domain trainer, and native multilingual support. Oracle Digital Assistant is open, scalable, and secure. It provides multi-channel support, automated bot-to-agent transfer, and integrated authentication profile. 04:56 Nikita: And what about the architecture? What happens at the back end? Chaitanya: Developers assemble digital assistants from one or more skills. Skills can be based on prebuilt skills provided by Oracle or third parties, custom developed, or based on one of the many skill templates available. 05:16 Lois: Chaitanya, what exactly are “skills” within the Oracle Digital Assistant framework?  Chaitanya: Skills are individual chatbots that are designed to interact with users and fulfill specific type of tasks. Each skill helps a user complete a task through a combination of text messages and simple UI elements like select list. When a user request is submitted through a channel, the Digital Assistant routes the user's request to the most appropriate skill to satisfy the user's request. Skills can combine multilingual NLP deep learning engine, a powerful dialogflow engine, and integration components to connect to back-end systems.  Skills provide a modular way to build your chatbot functionality. Now users connect with a chatbot through channels such as Facebook, Microsoft Teams, or in our case, Oracle APEX chatbot, which is embedded into an APEX application. 06:21 Nikita: That’s fascinating. So, what are some use cases of Oracle Digital Assistant in APEX apps? Chaitanya: Digital assistants streamline approval processes by collecting information, routing requests, and providing status updates. Digital assistants offer instant access to information and documentation, answering common questions and guiding users. Digital assistants assist sales teams by automating tasks, responding to inquiries, and guiding prospects through the sales funnel. Digital assistants facilitate procurement by managing orders, tracking deliveries, and handling supplier communication. Digital assistants simplify expense approvals by collecting reports, validating receipts, and routing them for managerial approval. Digital assistants manage inventory by tracking stock levels, reordering supplies, and providing real-time inventory updates. Digital assistants have become a common UX feature in any enterprise application. 07:28 Want to learn how to design stunning, responsive enterprise applications directly from your browser with minimal coding? The new Oracle APEX Developer Professional learning path and certification enables you to leverage AI-assisted development, including generative AI and Database 23ai, to build secure, scalable web and mobile applications with advanced AI-powered features. From now through May 15, 2025, we’re waiving the certification exam fee (valued at $245). So, what are you waiting for? Visit mylearn.oracle.com to get started today. 08:09 Nikita: Welcome back! Thanks for that, Chaitanya. Toufiq, let’s talk about the OCI Document Understanding service. What is it? Toufiq: Using this service, you can upload documents to extract text, tables, and other key data. This means the service can automatically identify and extract relevant information from various types of documents, such as invoices, receipts, contracts, etc. The service is serverless and multitenant, which means you don't need to manage any servers or infrastructure. You can access this service using the console, REST APIs, SDK, or CLI, giving you multiple ways to integrate. 08:55 Nikita: What do we use for APEX apps?  Toufiq: For APEX applications, we will be using REST APIs to integrate the service. Additionally, you can process individual files or batches of documents using the ProcessorJob API endpoint. This flexibility allows you to handle different volumes of documents efficiently, whether you need to process a single document or thousands at once. With these capabilities, the OCI Document Understanding service can significantly streamline your document processing tasks, saving time and reducing the potential for manual errors. 09:36 Lois: Ok.  What are the different types of models available? How do they cater to various business needs? Toufiq: Let us start with pre-trained models. These are ready-to-use models that come right out of the box, offering a range of functionalities. The available models are Optical Character Recognition (OCR) enables the service to extract text from documents, allowing you to digitize, scan the documents effortlessly. You can precisely extract text content from documents. Key-value extraction, useful in streamlining tasks like invoice processing. Table extraction can intelligently extract tabular data from documents. Document classification automatically categorizes documents based on their content. OCR PDF enables seamless extraction of text from PDF files. Now, what if your business needs go beyond these pre-trained models. That's where custom models come into play. You have the flexibility to train and build your own models on top of these foundational pre-trained models. Models available for training are key value extraction and document classification. 10:50 Nikita: What does the architecture look like for OCI Document Understanding? Toufiq: You can ingest or su

Get ready to explore how generative AI is transforming development in Oracle APEX. In this episode, hosts Lois Houston and Nikita Abraham are joined by Oracle APEX experts Apoorva Srinivas and Toufiq Mohammed to break down the innovative features of APEX 24.1. Learn how developers can use APEX Assistant to build apps, generate SQL, and create data models using natural language prompts.   Oracle APEX: Empowering Low Code Apps with AI: https://mylearn.oracle.com/ou/course/oracle-apex-empowering-low-code-apps-with-ai/146047/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Nikita: Welcome back to another episode of the Oracle University Podcast! I’m Nikita Abraham, Team Lead of Editorial Services with Oracle University, and I’m joined by Lois Houston, Director of Innovation Programs. Lois: Hi everyone! In our last episode, we spoke about Oracle APEX and AI. We covered the data and AI -centric challenges businesses are up against and explored how AI fits in with Oracle APEX. Niki, what’s in store for today? Nikita: Well, Lois, today we’re diving into how generative AI powers Oracle APEX. With APEX 24.1, developers can use the Create Application Wizard to tell APEX what kind of application they want to build based on available tables. Plus, APEX Assistant helps create, refine, and debug SQL code in natural language. 01:16 Lois: Right. Today’s episode will focus on how generative AI enhances development in APEX. We’ll explore its architecture, the different AI providers, and key use cases. Joining us are two senior product managers from Oracle—Apoorva Srinivas and Toufiq Mohammed. Thank you both for joining us today. We’ll start with you, Apoorva. Can you tell us a bit about the generative AI service in Oracle APEX? Apoorva: It is nothing but an abstraction to the popular commercial Generative AI products, like OCI Generative AI, OpenAI, and Cohere. APEX makes use of the existing REST infrastructure to authenticate using the web credentials with Generative AI Services. Once you configure the Generative AI Service, it can be used by the App Builder, AI Assistant, and AI Dynamic Actions, like Show AI Assistant and Generate Text with AI, and also the APEX_AI PL/SQL API. You can enable or disable the Generative AI Service on the APEX instance level and on the workspace level. 02:31 Nikita: Ok. Got it. So, Apoorva, which AI providers can be configured in the APEX Gen AI service? Apoorva: First is the popular OpenAI. If you have registered and subscribed for an OpenAI API key, you can just enter the API key in your APEX workspace to configure the Generative AI service. APEX makes use of the chat completions endpoint in OpenAI. Second is the OCI Generative AI Service. Once you have configured an OCI API key on Oracle Cloud, you can make use of the chat models. The chat models are available from Cohere family and Meta Llama family.  The third is the Cohere. The configuration of Cohere is similar to OpenAI. You need to have your Cohere OpenAI key. And it provides a similar chat functionality using the chat endpoint.  03:29 Lois: What is the purpose of the APEX_AI PL/SQL public API that we now have? How is it used within the APEX ecosystem? Apoorva: It models the chat operation of the popular Generative AI REST Services. This is the same package used internally by the chat widget of the APEX Assistant. There are more procedures around consent management, which you can configure using this package. 03:58 Lois: Apoorva, at a high level, how does generative AI fit into the APEX environment? Apoorva: APEX makes use of the existing REST infrastructure—that is the web credentials and remote server—to configure the Generative AI Service. The inferencing is done by the backend Generative AI Service. For the Generative AI use case in APEX, such as NL2SQL and creation of an app, APEX performs the prompt enrichment.  04:29 Nikita: And what exactly is prompt enrichment? Apoorva: Let's say you provide a prompt saying "show me the average salary of employees in each department." APEX will take this prompt and enrich it by adding in more details. It elaborates on the prompt by mentioning the requirements, such as Oracle SQL syntax statement, and providing some metadata from the data dictionary of APEX. Once the prompt enrichment is complete, it is then passed on to the LLM inferencing service. Therefore, the SQL query provided by the AI Assistant is more accurate and in context.  05:15 Unlock the power of AI Vector Search with our new course and certification. Get more accurate search results, handle complex datasets easily, and supercharge your data-driven decisions. From now to May 15, 2025, we are waiving the certification exam fee (valued at $245). Visit mylearn.oracle.com to enroll. 05:41  Nikita: Welcome back! Let’s talk use cases. Apoorva, can you share some ways developers can use generative AI with APEX? Apoorva: SQL is an integral part of building APEX apps. You use SQL everywhere. You can make use of the NL2SQL feature in the code editor by using the APEX Assistant to generate SQL queries while building the apps. The second is the prompt-based app creation. With APEX Assistant, you can now generate fully functional APEX apps by providing prompts in natural language. Third is the AI Assistant, which is a chat widget provided by APEX in all the code editors and for creation of apps. You can chat with the AI Assistant by providing your prompts and get responses from the Generative AI Services. 06:37 Lois: Without getting too technical, can you tell us how to create a data model using AI? Apoorva: A SQL Workshop utility called Create Data Model Using AI uses AI to help you create your own data model. The APEX Assistant generates a script to create tables, triggers, and constraints in either Oracle SQL or Quick SQL format. You can also insert sample data into these tables. But before you use this feature, you must create a generative AI service and enable the Used by App Builder setting. If you are using the Oracle SQL format, when you click on Create SQL Script, APEX generates the script and brings you to this script editor page. Whereas if you are using the Quick SQL format, when you click on Review Quick SQL, APEX generates the Quick SQL code and brings you to the Quick SQL page. 07:39 Lois: And to see a detailed demo of creating a custom data model with the APEX Assistant, visit mylearn.oracle.com and search for the "Oracle APEX: Empowering Low Code Apps with AI" course. Apoorva, what about creating an APEX app from a prompt. What’s that process like? Apoorva: APEX 24.1 introduces a new feature where you can generate an application blueprint based on a prompt using natural language. The APEX Assistant leverages the APEX Dictionary Cache to identify relevant tables while suggesting the pages to be created for your application. You can iterate over the application design by providing further prompts using natural language and then generating an application based on your needs. Once you are satisfied, you can click on Create Application, which takes you to the Create Application Wizard in APEX, where you can further customize your application, such as application icon and other features, and finally, go ahead to create your application. 08:53 Nikita: Again, you can watch a demo of this on MyLearn. So, check that out if you want to dive deeper.  Lois: That’s right, Niki. Thank you for these great insights, Apoorva! Now, let's turn to Toufiq. Toufiq, can you tell us more about the APEX Assistant feature in Oracle APEX. What is it and how does it work? Toufiq: APEX Assistant is available in Code Editors in the APEX App Builder. It leverages generative AI services as the backend to answer your questions asked in natural language. APEX Assistant makes use of the APEX dictionary cache to identify relevant tables while generating SQL queries. Using the Query Builder mode enables Assistant. You can generate SQL queries from natural language for Form, Report, and other region types which support SQL queries. Using the general assistance mode, you can generate PL/SQL JavaScript, HTML, or CSS Code, and seek further assistance from generative AI. For example, you can ask the APEX Assistant to optimize the code, format the code for better readability, add comments, etc. APEX Assistant also comes with two quick actions, Improve and Explain, which can help users improve and understand the selected code. 10:17 Nikita: What about the Show AI Assistant dynamic action? I know that it provides an AI chat interface, but can you tell us a little more about it?  Toufiq: It is a native dynamic action in Oracle APEX which renders an AI chat user interface. It leverages the generative AI services that are configured under Workspace utilities. This AI chat user interface can be rendered inline or as a dialog. This dynamic action also has configurable system prompt and welcome message attributes.  10:52 Lois: Are there attributes you can configure to leverage even more customization?  Toufiq: The first attribute is the initial prompt. The initial prompt represents a message as if it were coming from the user. This can either be a specific item value or a value derived from a JavaScript expression. The next attribute is use response. This attribute determines how the AI Assistant should return responses. The term response refers to the message content of an individual chat message. You ha

Lois Houston and Nikita Abraham kick off a new season of the podcast, exploring how Oracle APEX integrates with AI to build smarter low-code applications. They are joined by Chaitanya Koratamaddi, Director of Product Management at Oracle, who explains the basics of Oracle APEX, its global adoption, and the challenges it addresses for businesses managing and integrating data. They also explore real-world use cases of AI within the Oracle APEX ecosystem   Oracle APEX: Empowering Low Code Apps with AI: https://mylearn.oracle.com/ou/course/oracle-apex-empowering-low-code-apps-with-ai/146047/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -----------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! Thank you for joining us as we begin a new season of the podcast, this time focused on Oracle APEX and how it integrates with AI to help you create powerful applications. This season is for everyone—from beginners and SQL developers to DBA data scientists and low-code enthusiasts. So, if you’re interested in using Oracle APEX to build low-code applications that have custom generative AI features, you’ll want to stay tuned in. 01:07 Lois: That’s right, Niki. Today, we're going to discuss Oracle APEX at a high level, starting with what it is. Then, we’ll cover a few business challenges related to data and AI innovation that organizations face, and learn how the powerful combination of APEX and AI can help overcome these challenges.  01:27 Nikita: To take us through it all, we’ve got Chaitanya Koratamaddi with us. Chaitanya is Director of Product Management for Oracle APEX. Hi Chaitanya! For anyone new to Oracle APEX, can you explain what it is and why it's so widely used? Chaitanya: Oracle APEX is the world's most popular enterprise low code application platform. APEX enables you to build secure and scalable enterprise-scale applications with world class features that can be deployed anywhere, cloud or on-premises. And with APEX, you can build applications 20 times faster with 100 times less code. APEX delivers the most productive way to develop and deploy mobile and web applications everywhere. 02:18 Lois: That’s impressive. So, what’s the adoption rate like for Oracle APEX? Chaitanya: As of today, there are 19 million plus APEX applications created globally. 5,000 plus APEX applications are created on a daily basis and there are 800,000 plus APEX developers worldwide. 60,000 plus customers in 150 countries across various industry verticals. And 75% of Fortune 500 companies use Oracle APEX. 02:56 Nikita: Wow, the numbers really speak for themselves, right? But Chaitanya, why are organizations adopting Oracle APEX at this scale? Or to put it differently, what’s the core business challenge that Oracle APEX is addressing? Chaitanya: From databases to all data, you know that the world is more connected and automated than ever. To drive new business value, organizations need to explore and exploit new sources of data that are generated from this connected world. That can be sounds, feeds, sensors, videos, images, and more. Businesses need to be able to work with all types of data and also make sure that it is available to be used together. Typically, businesses need to work on all data at a massive scale. For example, supply chains are no longer dependent just on inventory, demand, and order management signals. A manufacturer should be able to understand data describing global weather patterns and how it impacts their supply chains. Businesses need to pull in data from as many social sources as possible to understand how customer sentiment impacts product sales and corporate brands. Our customers need a data platform that ensures all this data works together seamlessly and easily. 04:38 Lois: So, you’re saying Oracle APEX is the platform that helps businesses manage and integrate data seamlessly. But data is just one part of the equation, right? Then there’s AI. How are the two related?  Chaitanya: Before we start talking about Oracle AI, let's first talk about what customers are looking for and where they are struggling within their AI innovation. It all starts with data. For decades, working with data has largely involved dealing with structured data, whether it is your customer records in your CRM application and orders from your ERP database. Data was organized into database and tables, and when you needed to find some insights in your data, all you need to do is just use stored procedures and SQL queries to deliver the answers. But today, the expectations are higher. You want to use AI to construct sophisticated predictions, find anomalies, make decisions, and even take actions autonomously. And the data is far more complicated. It is in an endless variety of formats scattered all over your business. You need tools to find this data, consume it, and easily make sense of it all. And now capabilities like natural language processing, computer vision, and anomaly detection are becoming very essential just like how SQL queries used to be. You need to use AI to analyze phone call transcripts, support tickets, or email complaints so you can understand what customers need and how they feel about your products, customer service, and brand. You may want to use a data source as noisy and unstructured as social media data to detect trends and identify issues in real time.  Today, AI capabilities are very essential to accelerate innovation, assess what's happening in your business, and most importantly, exceed the expectations of your customers. So, connecting your application, data, and infrastructure allows everyone in your business to benefit from data. 07:32 Raise your game with the Oracle Cloud Applications skills challenge. Get free training on Oracle Fusion Cloud Applications, Oracle Modern Best Practice, and Oracle Cloud Success Navigator. Pass the free Oracle Fusion Cloud Foundations Associate exam to earn a Foundations Associate certification. Plus, there’s a chance to win awards and prizes throughout the challenge! What are you waiting for? Join the challenge today by visiting oracle.com/education. 08:06 Nikita: Welcome back! So, let’s focus on AI across the Oracle Cloud ecosystem. How does Oracle bring AI into the mix to connect applications, data, and infrastructure for businesses? Chaitanya: By embedding AI throughout the entire technology stack from the infrastructure that businesses run on through the applications for every line of business, from finance to supply chain and HR, Oracle is helping organizations pragmatically use AI to improve performance while saving time, energy, and resources.  Our core cloud infrastructure includes a unique AI infrastructure layer based on our supercluster technology, leveraging the latest and greatest hardware and uniquely able to get the maximum out of the AI infrastructure technology for scenarios such as large language processing. Then there is generative AI and ML for data platforms. On top of the AI infrastructure, our database layer embeds AI in our products such as autonomous database. With autonomous database, you can leverage large language models to use natural language queries rather than writing a SQL when interacting with the autonomous database. This enables you to achieve faster adoption in your application development. Businesses and their customers can use the Select AI natural language interface combined with Oracle Database AI Vector Search to obtain quicker, more intuitive insights into their own data. Then we have AI services. AI services are a collection of offerings, including generative AI with pre-built machine learning models that make it easier for developers to apply AI to applications and business operations. The models can be custom-trained for more accurate business results. 10:17 Nikita: And what specific AI services do we have at Oracle, Chaitanya?  Chaitanya: We have Oracle Digital Assistant Speech, Language, Vision, and Document Understanding. Then we have Oracle AI for Applications. Oracle delivers AI built for business, helping you make better decisions faster and empowering your workforce to work more effectively. By embedding classic and generative AI into its applications, Fusion Apps customers can instantly access AI outcomes wherever they are needed without leaving the software environment they use every day to power their business. 11:02 Lois: Let’s talk specifically about APEX. How does APEX use the Gen AI and machine learning models in the stack to empower developers. How does it help them boost productivity? Chaitanya: Starting APEX 24.1, you can choose your preferred large language models and leverage native generative AI capabilities of APEX for AI assistants, prompt-based application creation, and more. Using native OCI capabilities, you can leverage native platform capabilities from OCI, like AI infrastructure and object storage, etc. Oracle APEX running on autonomous infrastructure in Oracle Cloud leverages its unique native generative AI capabilities tuned specifically on your data. These language models are schema aware, data aware, and take into account the shape of information, enabling your applications to take advantage of large language models pre-trained on your unique data. You can give your