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 catalogs

We talked about a data lake in AWS being a combination of the data in S3 buckets and the metadata of this data stored in a catalog. We will solve the mystery of creating a technical catalog in AWS by introducing another critical service for building a modern data platform, AWS Glue—a serverless data integration service. Now, Glue is actually an umbrella service consisting of multiple parts. It has the Glue ETL part, which is used for building data integration work, and we have multiple chapters on data ingestion and integration. The component of Glue that is relevant to our data catalog discussion is Glue Data Catalog. Let’s unfold more about the catalog in Glue and how it helps with our data lake in S3.

Glue Data Catalog

As the data passes through layers of the data lake in S3, the metadata of the data is captured and stored in Glue Data Catalog. It creates and stores the technical metadata in the form of data definition language (DDL) statements...