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

Transactional data lakes

Let’s introduce this topic with a use case from GreatFin.

Use case for a transactional data lake

GreatFin wants to comply with the right to be forgotten General Data Protection Regulation (GDPR) compliance in Europe. It wants to have the ability in all its systems, including its analytics environments, to easily locate, update, or delete records as and when required.

The need to create transactional data lakes came about due to many business use cases and the challenges associated with them, such as the following:

Use Case

Challenge

Compliance requirements

Compliance and privacy laws—for example, the GDPR requires the deletion of certain data within a specific timeframe and/or across all datasets

Change data capture (CDC)

CDC from the source databases and incremental...