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

External data sharing

Every organization produces and collects a lot of data. Often, data that’s produced is consumed for internal operations, but there are many cases where some data that’s collected can be monetized by offering it to other companies that can use this data to enrich their analytical insights. As you may recall from our data lake chapter, we created an enriched layer for data that could use a combination of internal data and external data to produce datasets that help derive precision insights.

Creating a vision for sharing data externally to make money is easy; however, the real challenge is around setting up all the mechanisms to do this in a scalable, secure, and cost-effective manner. Creating a secure and optimal technical handshake between the data providers and data consumers is not easy. Producers and subscribers both want a secure and easy-to-use cloud-native platform that can seamlessly enable data sharing by providing self-service options...