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

Putting it all together

So far, we have discussed the different storage layers in a typical data lake in S3 and defined the purpose of each of the layers. We also introduced the concept of creating metadata using a Glue crawler and storing it in Glue Data Catalog. Finally, we looked at use cases for building transactional data lakes. This is a good time to pivot back to the GreatFin business requirements we introduced earlier and apply these data lake foundational concepts to our use case.

Marketing use case

Suppose the marketing department at GreatFin wants to find certain top leads for offering a new type of certificate of deposit (CD) with a higher interest rate to select a few high-net-worth customers only. In this case, the customer data will be stored in multiple systems, from different LOBs.

Let’s walk through what each layer in the data lake might look like.

Raw layer example

The following diagram is a depiction of data stored in a raw layer bucket in...