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

Operational Analytics

Every business performs certain operations to generate revenue. All these operations eventually generate lots of data, across multiple systems. Many organizations perform operations via the digital space by providing a variety of software applications. All these applications perform a ton of operational logs on the systems they are hosted on. There is a wealth of information in these log files – system errors, performance statistics, security aspects, network traffic patterns, customer information, and so forth. Across all these applications on multiple systems, the amount of daily log data that’s generated can be overwhelming to store, manage, and analyze to get insights from it. Finding relevant pieces of information across all these logs is like finding a needle in a haystack.

To solve this problem of analyzing log data, there needs to be a suitable technology and supporting toolset that can help index all this data and make it easy to search...