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 looked at how you can migrate data in batches into different AWS storage systems, especially a data lake in S3. Data ingestion is mostly the first step in data migration, and it can get really complicated if the correct set of tools is not leveraged for appropriate source and target data stores.

We also looked at how you can use DMS and SCT to migrate/replicate on-prem databases into AWS data stores and how you can bring over data into the data lake built on S3. We then looked at how you can use AppFlow to migrate data from SaaS-based applications into the data lake. We also looked at how the versatility of Glue ETL helps during the initial data ingestion stage. And finally, we looked at all the other storage and file transfer services, including DataSync, Transfer Family, and Snow Family.

This brings us to the end of an important chapter where we were able to hydrate data stores in AWS with purpose-built modern data ingestion services. Since this...