This episode digs into Amazon EventBridge. What is it? What does it do for you? Why would you want to use it.
In this In Real Life episode we interview John Moberg of Conductive Digital. John has over 25 years’ experience as an executive leader and entrepreneur. During this time he has successfully blended technology and business needs with many companies including: Allegiant Utility Services, Concord Utility Services, UnitedHealthcare, Best Buy, Geek Squad, 3M, Royal Bank of Canada, Intel, Jamba Juice, and Caribou Coffee.His most recent endeavor directly benefits the Utility industry. As ...
In this episode we review some of the interesting data processing announcements that came out of AWS re:Invent 2022.
This episode of AWS re:View is part 2 of a deep dive into the capabilities of Amazon Simple Storage Service (S3). We will review a number of the standard, and unique, capabilities of S3 and discuss some interesting possibilities these capabilities enable.
Welcome to the November 2022 Update Show We are going to share some of the interesting updates from the last month and discuss some of the interesting impacts they may have.
This episode of AWS re:View is a deep dive into the capabilities of Amazon Simple Storage Service (S3). We will review a number of the standard, and unique, capabilities of S3 and discuss some interesting possibilities these capabilities enable. This is part 1 of a two part episode.
Today we introduce a new type of episode on AWS re:View, the "In Real Life" (IRL) episode. In these episodes, we will interview guests who are building with AWS. We will hear about how they are using AWS, their successes and struggles, as well as their lessons learned.In this, our first IRL episode, we interview Aaron Decker, the Head of Engineering at Bounty (www.bounty.co).
In this episode of AWS re:View we review the various features and capabilities of AWS Glue in more depth. We touch on topics from data catalog, to automation, to data transformation.
Welcome to a new format. This is our first ever AWS update show. We are going to share some of the interesting updates from the last month and discuss some of the interesting impacts they may have.
In this episode we will introduce some of the tools available on AWS that help improve application code development, quality management, and deployment. Topics will include Code Guru, Code Whisperer, Cloud9, SAM (Serverless Application Model), and CodePipeline.
In this episode we take a look at options for executing ML workloads on AWS. We will review what is available within the Amazon SageMaker toolset and what you can do outside of it.
In this episode we look at Amazon SageMaker and how it can be used to develop and deploy machine learning models.
In this episode we look a the process of data science on AWS. How does it start? How should it be approached? What are the steps you should follow?
In this episode we take a look at AWS’ offerings around learning in the area of AI/ML. We review the formal class offerings as well as look at the hands on programs like DeepRacer. If you are just getting into AI/ML then this episode will be a great starting place.
This episode is a survey of the pre-trained AI/ML services provided by AWS. We define each one and provide examples of use.
In this episode, we dig into AWS Data Exchange. We will discuss the value of AWS Data Exchange, the marketplace and what's available on it, and how you can leverage it both to enhance your analytics and to share your data with others in a managed way.
In this episode we dig into the tools available in the AWS ecosystem for interactive data analysis. We look at QuickSight, DataBrew, Sagemaker Canvas, and use of Jupyter Notebooks.
This episode examined the myriad of ways that you can pull data into AWS for all types of processing. We looked at both batch and real-time approaches to data ingestion.
In this episode, we looked at AWS' capabilities for querying across multiple data sources. What are they? When are they best used? Where do we speculate they will go in the future?
This session of AWS re:View dug into the tools provided by AWS for transforming and curating data. We discussed the different options for manipulating data on AWS and the pros and cons of each. When each shines and when to avoid it. This will cover many items including AWS Glue (Jobs, DataBrew, etc.), SQL, EMR, Lambda, and more.