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 collaborations with partners using AWS Clean Rooms

Collaborating on shared datasets while safeguarding the underlying raw data poses a common challenge for companies and their partners. Organizations often encounter data fragmentation across various applications, channels, departments, and partner networks, leading to interoperability and scalability issues. Numerous organizations seek improved methods for managing the collection, storage, and utilization of sensitive raw data while ensuring data privacy.

However, the methods that are traditionally used to utilize data in collaboration with partners can conflict with the objective of data protection. In certain cases, these methods have necessitated companies to share copies of their data with partners and rely on contractual agreements to prevent misuse. However, customers prefer to minimize data movement to safeguard their information, prevent misuse, and mitigate the risks of data leaks. Consequently, they often opt against...