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

The need for automation

Even though we have come to the last chapter of the book, a data platform cannot be sustainable in the long run if a large number of teams manually manage all the day-to-day operations. In a mature organization, personas who help build and operate the data platform do not get access to the AWS console in production. So, the main question arises: how do they manage and operate a modern data platform? The answer is simple – each and every aspect of the data platform is managed and operated through automation scripts and pipelines.

Before we dive into what automation entails, let’s quickly highlight why automation is needed in the first place.

Automation plays a crucial role in an analytics platform on AWS for several reasons:

  • Efficiency: Automation eliminates manual, repetitive tasks, allowing analytics processes to run more efficiently. It reduces the time and effort required to perform data ingestion, transformation, modeling, and...