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 data federation helps organizations quickly fetch data using a single pane of glass from multiple heterogeneous source systems.

We looked at how different connectors in Amazon Athena allow for a quick and easy way to join datasets from other sources. Athena’s connectors make it a seamless and transparent user experience where reports can be created just by writing SQL statements inside Athena, to join datasets from the underlying data stores.

We also looked at how Amazon Redshift can assist in federated queries, by fetching data stored in ODS systems such as MySQL and PostgreSQL. A use case that typically gets solved by this mechanism is querying live operational data that’s constantly getting updated in the ODS.

The next chapter is critical in our modern data platform journey as we will discuss everything about predictive analytics and how it helps organizations think big with their data.