Preface

Many IT leaders and professionals know how to get data in a particular type of database and derive value from it. But when it comes to creating an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, it is always challenging to design and implement such a platform.

This book covers end-to-end solutions of many of the common data, analytics and AI/ML use-cases that organizations want to solve using AWS services. The book systematically lays out all the building blocks of a modern data platform including data lake, data warehouse, 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 many of the AWS services to create a scalable, flexible, performant and cost-effective modern data platform.

By the end of this book, readers will be equipped with all the necessary architecture patterns and would be able to apply this knowledge to build a modern data platform for their organization using AWS services.