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 resolution with AWS Entity Resolution

The best way to explain this topic would be to take the example of data at GreatFin, the example company we have been using in this book for use cases. GreatFin has data coming in from multiple LOBs. All LOBs have overlapping customer information. Sometimes, customers update details with one LOB but other LOBs don’t always see that update. This eventually creates a web of conflicting information across the enterprise where a golden version of truth for a customer or any other entity doesn’t exist. This is where inaccuracies arise in the operational systems as well as in the analytical environments. All organizations strive to create a golden or a master copy of their entities.

The following figure highlights the efforts of organizations to create a golden copy of the entity from across multiple sources of data:

Figure 14.41 – Entity resolution process

Figure 14.41 – Entity resolution process

Let’s introduce the service...