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

Data mesh concepts

If you recall from Chapter 8, Data Sharing, we kept the important topic of a distributed data lake that spans multiple AWS accounts open-ended. Now is a good time to complete that story. Even today, the vast majority of use cases that require a data lake can be solved by building a centralized data lake. However, as organizations become bigger, new lines of businesses (LOBs) that work as autonomous units become a reality. All these LOBs add more data sources to grow their business units, resulting in the exponential growth of data at the enterprise level.

Sharing data within an enterprise presents its fair share of challenges. Different LOBs have invested in cloud-based data lakes, along with customized analytics solutions, tailored to address their specific business needs. However, these systems are often designed to cater to particular types of data and may not seamlessly translate to other problem domains.

For many large organizations with many LOBs, a centralized...