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 Warehousing

In this chapter, we will look at the following key topics:

  • The need for a data warehouse
  • Data warehousing using Amazon Redshift
  • Data warehouse modernization with Redshift
  • Data ingestion patterns
  • Data transformation using ELT patterns
  • Data security and governance patterns
  • Data consumption patterns

The concept of data warehouses has existed for a long time and organizations have been able to use data warehouse systems to do online analytics processing (OLAP). Deriving analytical insights from the data from these systems is the main goal of every organization. However, as we discussed in Chapter 1, the traditional data warehouse setup became challenging in the age of cloud computing. With the ever-growing volume, velocity, and variety of data in recent times, traditional on-premises data warehouses are not able to handle all the new use cases businesses users wish to solve.