Book Image

Modern Data Architecture on AWS

By : Behram Irani
5 (1)
Book Image

Modern Data Architecture on AWS

5 (1)
By: Behram Irani

Overview of this book

Many IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.
Table of Contents (24 chapters)
1
Part 1: Foundational Data Lake
5
Part 2: Purpose-Built Services And Unified Data Access
17
Part 3: Govern, Scale, Optimize And Operationalize

Summary

In this chapter, we explored the latest trend around GenAI and how it is changing the ways businesses think about solving their use cases. We went through a range of possible use cases that each industry can solve using GenAI. We also looked at how FMs and LLMs are the core drivers for achieving GenAI outcomes.

We then pivoted toward how AWS helps organizations use GenAI for their use cases. Amazon Bedrock is a service that simplifies building and deploying GenAI applications using FMs in AWS. Purpose-built accelerators, such as AWS Trainum, are used for cost-effectively training LLMs, and AWS Inferentia and Inferentia2 are used to achieve best-in-class price performance to draw inferences from the FM models. Dedicated GenAI applications such as Amazon CodeWhisperer can help boost the productivity of the development team by auto-generating code. AWS also provides the flexibility to search for and choose from many of the FMs available in the market by using SageMaker JumpStart...