Everything Data Analytics

Before any fruit and vegetables are sold in supermarkets, they are first harvested from various farms and orchards. Then, they are sorted into their respective categories, cleaned to remove any bacteria and soil, and packaged uniformly during the preparation stage. Finally, depending on store orders, they are sent out to various locations. In the data analytics world, raw data goes through a similar process before it can be analyzed and reported on — and this is where ETL comes in.  There are three main steps in the ETL process — Extract, Transform, and Load.  Together, they work to prepare your raw data for analysis and reporting. Check out the video to learn more about the ETL process: https://youtu.be/kmS7nMK2_3k ETL (Extract, Transform, Load) Part 1: https://youtu.be/CyVvglLMLew For more info on ETL, visit: https://cubeware.com/  Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

In the food industry, quality control ensures that the meat, bread, and other edible items reaching you are of the best quality. Companies use various ways to manage this, from developing fixed product formulations to standardizing manufacturing processes. By following these procedures, the quality of food is kept consistent and reliable for the consumers. In the same way, companies also need to manage and control the quality of their data. This has become increasingly important due to the enormous amount of data that’s become available and accessible in the recent decade. As a company’s datasets grow, it’s critical to ensure that they are consistent and accurate for analyses and insights. After all, data-driven decisions are only as good as the data itself. With datasets regarding customers, finance, operations, and sales comprising the core of most organizations, Data Quality and Data Quality Management only become more vital. In this three-part series, we’ll be covering what Data Quality is, what Data Quality Management is, as well as why both are important. Check out the video to learn more about What is Data Quality? : https://youtu.be/LnEzrC0FnZc  For more info on ETL, visit: https://www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

ETL is defined as a method or process of extracting, transforming, and loading raw data from various sources into a single and centralized location. These can be data warehouses or other centralized data storage systems. In the data analytics world, raw data goes through a similar process before it can be analyzed and reported — and this is where ETL comes in. So, let’s take a look at what ETL means. Check out the video to learn more about the ETL process: https://youtu.be/CyVvglLMLew For more info on ETL, visit: https://www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

What do you do when you outgrow your reporting system? Meet Farmer X. They’re a manufacturer and distributor of organic foods. However, over the last decade, Farmer X experienced a huge sales growth — this was not so great for their reporting system, which was all completed on cloud-based spreadsheet applications. With the Cubeware Cockpit, Farmer X was able to complete analyses and generate reports — both planned and ad-hoc — with swift accuracy, detail, flexibility, and transparency.  Not only did this free up Farmer X’s budget, resources, and time from manual reporting, but the employees of Farmer X were finally able to focus on bringing their visualizations to life. Check out the video to learn more about Farmer X's success story: https://youtu.be/0iQHPEoRwzM To learn more about the Cubeware Solutions Platform and its applications, click here: https://www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

What do people mean when they refer to Dark Data? And how is Dark Data different from regular data?  Almost everything we do involves data —we’re either generating it or receiving it, whether we’re aware of it or not. And this adds up to, well, a lot of data — and to no one’s surprise, a lot of it is left unused.  In short, Dark Data refers to the data that we often collect but do not use, especially for Business Intelligence purposes.  Often times, Dark Data is what leads to businesses experiencing the DRIP syndrome, which stands for Data Rich, Information Poor. This happens when companies gather a lot of data but don't have the tools in place to turn it into valuable information.  Well, we’ve got a lot to cover so let’s dive into more detail as to what Dark Data is and what its advantages and disadvantages are. Check out the video to learn more about Dark Data: https://youtu.be/pbNUZU-FaSA To learn more about the Cubeware Solutions Platform and its applications, click here: https://www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

In our two previous videos, we discussed what Prescriptive Analytics is, how it works, and what its examples look like. To check them out,   [What is Prescriptive Analytics?: Part 1] https://youtu.be/pzvT6Z_b6MA [Examples of Prescriptive Analytics: Part 2] https://youtu.be/NOo8Nc9zG20  Despite being a pivotal advanced analytical approach, Prescriptive Analytics isn’t commonly implemented as it requires an assortment of tools and a complex understanding of the method. Companies that do employ Prescriptive Analytics, however, are able to achieve stronger goals by understanding how different actions result in different outcomes. Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Prescriptive Analytics is a type of data analytics that recommends a course of action users should take in order to achieve a desired outcome or goal. It comes after the stages of descriptive and predictive analytics.  For more info on data analytics, visit our website at www.cubeware.com What is Prescriptive Analytics? [PART 1] What Are Examples of Prescriptive Analytics? [PART 2] Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Prescriptive Analytics is a type of data analytics that recommends a course of action users should take in order to achieve a desired outcome or goal. It comes after the stages of descriptive and predictive analytics. For more info on data analytics, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

You share a lot of data with a lot of companies — these collected datasets need to be stored securely to prevent any cases of stolen, misused, deleted, or altered data.    Many businesses today have migrated to the digital landscape, rendering it especially critical that they implement measures that protect their digital assets. After all, companies used to protect their physical assets, so now it's time they learn to do the same with their digital ones.   In this podcast, we’ll cover what Data Security is, what its solutions look like, and why it’s important. For more info on data analytics, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

During the 2012 Brazilian Grand Prix, Sebastian Vettel was in the running to win the World Championship for the 3rd time. However, during this decisive race, Vettel’s car was hit from the back early on. If this were any other sport, the competition would have been over. However, Vettel’s analysts and engineers swooped in the moment the impact occurred. Teams of analysts spanning across continents work together in real-time on data analytics to churn out insights and solutions. So, let’s dive into how Data Analytics was used to help Sebastian Vettel clinch his 3rd Championship. For more info on data analytics, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

When we think of mining, it sounds manual, tedious, and unfruitful — after all, hacking away at rock walls for hours on end hoping to find gold sounds like a lot of work for a very small reward.    Data Mining, however, is quite the opposite — without doing much work at all, you can reap rewarding results. That’s because we have modern solutions which do it for us.  These softwares can sift through terabytes of data within minutes, giving us valuable insights on patterns, journeys, and relationships in the data.   So, let’s dive into what Data Mining is, how we do it, and what its examples look like. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Master Data Management, also called MDM, is a technology-enabled discipline describing how businesses utilize IT tools and solutions to govern, manage, use, and share their data. As businesses scale and grow in size, the number of applications and systems used across the board will also grow. These additional databases cause a fracture in information as they create multiple versions of the same data, and there’s no way of pinpointing which version is outdated, incorrect, or incomplete. To resolve this problem, MDM ensures the uniformity, accuracy, stewardship, semantic consistency, and accountability of the shared Master Data assets. In short, MDM enables all the employees in a business to stay aligned.  So let’s take a deep dive into what Master Data is, and how it fits into Master Data Management. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Data Management is a set of practices that organize, refine, and store your data. These practices are broken down into 7 key types. Their collective goal is to produce data that is accurate, consistent, accessible, usable, and secured, rendering it conducive for data analytics and reporting down the line. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Deep Learning has substantially impacted the way technology is leveraged across various sectors and industries.   Chatbots have become integral to more and more service industries every day. Deep Neural Networks have rendered this possible, allowing Deep Learning to decipher, understand, and address the intent of the customer on the other end. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

AI technologies have gone as far as giving computers the ability to observe data, recognize patterns, predict future outcomes, and take action. Deep Learning is one of the key derivatives of AI – and with its smart-computing and self-learning abilities, it’s paving the way for the next digital revolution across a myriad of industries.  So, what exactly is Deep Learning? Deep Learning is a complex form of Artificial Intelligence that enables machines to process data and learn logical conclusions in a way that mimics the thought process of a human. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Machine Learning in itself is very complex and can be broken down differently depending on its variations. Generally, it is divided into categories according to their purpose. These are: · Supervised Learning · Unsupervised Learning · Reinforcement Learning For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: YouTube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Machine Learning is a branch of Artificial Intelligence that teaches computers to complete tasks that previously could have only been done by a human being. To give you a rough idea, take a look at self-driving cars, real-time speech translation, and traffic forecasting – these are all applications of artificial intelligence and its capabilities.   Firstly, it’s important to understand that Machine Learning is a core sub-area of Artificial Intelligence – it is a method of data analysis that automates analytical model building. In simple words, it is the process of teaching a computer system to accurately make predictions based on data it is given. The objective is to get the system to automatically learn from the data, identify patterns, make decisions, and adjust actions accordingly with minimal human assistance.   With the increase in readily available data, cheap and powerful computational processing, and affordable data storage, the demand for and importance of Machine Learning has also rocketed. As a technology, its automated processes help analyze huge sums of data, ultimately easing the tasks of data scientists. It has changed the way of prepping, extracting, and interpreting data by replacing the traditional statistical procedures with adding automation sets of generic methods.   By producing accurate results and analyses through the development of efficient algorithms and data-driven models with real-time processing, Machine Learning has enabled computer science, statistics, as well as other emerging applications, to propel forward in their respective industries. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: Youtube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ Telegram: https://t.me/cubeware #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Struggling To Become A Data-Driven Organisation? 20-40% of all health sector resources are wasted. GE estimated that a 1% efficiency gain could lead to more than $63 billion in global health care savings. With hospitals facing unprecedented cost pressures, tracking and optimising patient flow, treatment, and equipment use is becoming increasingly difficult. How could hospitals overcome their primary challenge of efficiently treating as many patients as they can while simultaneously improving the quality of care? This is where data analytics comes in handy. In 2011, a study by MIT Sloan School of Management found that businesses engaged in data-driven decision-making “have output and productivity that is 5-6% higher than what would be expected”. The beauty about the state of business intelligence and data analytics in 2020 is that technology makes it possible to measure, test, and improve almost everything within your business operations from your ad campaigns to real manufacturing costs, customer relationships, talent, and more. The right analytics tool can help you keep track of critical data and allow you to respond in real-time. But here’s the thing. If you’re struggling to make data analytics work for your organisation, and it feels like you’re fishing for insight in an overwhelming sea of data - you’re not alone. A recent survey of large enterprises found that less than 40% manage data as a business asset and only 31% considered their organisation data-driven. It doesn’t matter how much data you have. Without taking a strategic approach to learning from it and employing the right tools, you may squander time, attention and money only to find that you haven’t used your data to achieve anything great. Here are some steps you can take to help you cover your bases, gain clarity and work towards becoming a data-driven company. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: Youtube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

Late one evening you are conversing with a friend or a partner about the latest gadget, a holiday destination or the latest TV series that you’ve been meaning to binge-watch. Your smart devices are probably on the table or tucked away somewhere in your bag or pocket. The next day, you open your smartphone and it is filled with ads that are related to the topics you were conversing last night. How is this possible? Is your phone really listening to you? The simple answer is no! Your phone is not listening to you. The ads targeted and reached you though effective use of data analytics. Data analytics has become a very popular term across multiple industries, from automotive to logistics, ecommerce to healthcare. All of which have used data analytics to their advantage and excelled. For instance, one of the biggest ecommerce giants, Amazon, uses data to improve its business and the whole ecommerce experience. Among the myriad industries utilising data analytics, ecommerce stands out as one of the front runners, having been completely transformed by it. Useful insights from the customers are gathered and integrated to help businesses make better decisions. Useful insights include the customer’s web behavior, any events that have occurred in their lives, details on what led to the purchase, amongst others. Data has revolutionized the ecommerce industry and will continue to do so in the future. With all the data collected, businesses are able to personalize product recommendations specifically to each individual, having leverage over predictive forecasting provides insight into the customers’ behavior along with their shopping patterns, helps improve customers experiences, and prevents fraud among many other benefits. Data analytics has completely transformed ecommerce, and it is still evolving rapidly. Experts are constantly trying to look for fresh and innovative ways to leverage the data in hand. Thus, data analytics technologies are driving the phenomenal growth of the global ecommerce industry. For more info on data analytics, business intelligence and to learn how can it benefit your business, visit our website at www.cubeware.com Join Our Social Networks: Youtube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/ #BusinessIntelligence #DataAnalytics #AdvancedDataAnalytics #Cubeware

As a data solutions platform, Cubeware’s digital warehousing ecosystem let’s you view and interpret data, leading to valuable insights that can transform your business.   A Cubeware solution gives you instant access to all of your valuable data in a safe and secure ecosystem, with complete visibility of your information. The powerful insights gained allow for informed, calculated decision making, and can be used to transform your business.   For more info on Digital Warehousing,  visit: https://www.cubeware.com/en/solutions/applications/data-modelling-data-management/ Join Our Social Networks:  Youtube: https://www.youtube.com/Cubeware LinkedIn: https://www.linkedin.com/company/cubeware-gmbh  Facebook: https://www.facebook.com/cubeware.gmbh  Twitter: https://twitter.com/Cubeware Instagram: https://www.instagram.com/cubeware.gmbh/   #DataAnalytics #DataWarehouse #Datawarehousing #DataScience   Related Topics:   advanced analytics, data warehouse tutorial, data warehouse architecture, data warehouse concepts, what is data warehouse, sql data warehouse, olap in data warehouse, What is Data Warehouse, data warehouse, data warehouse definition, types of data warehouse, data warehouse vs database, data warehouse software, data warehousing, data warehousing tutorial, data warehouse basics, Introduction to Data warehouse, how data warehouse works, data warehouse implementations