Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services
Key Features
- Learn to build modern data platforms on AWS using data lakes and purpose-built data services
- Uncover methods of applying security and governance across your data platform built on AWS
- Find out how to operationalize and optimize your data platform on AWS
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
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.
What you will learn
- Familiarize yourself with the building blocks of modern data architecture on AWS
- Discover how to create an end-to-end data platform on AWS
- Design data architectures for your own use cases using AWS services
- Ingest data from disparate sources into target data stores on AWS
- Build data pipelines, data sharing mechanisms, and data consumption patterns using AWS services
- Find out how to implement data governance using AWS services
Who this book is for
This book is for data architects, data engineers, and professionals creating data platforms. The book's use case–driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner’s level understanding of AWS Cloud.
Table of Contents
- Modern Data Architecture on AWS
- Scalable Data Lakes
- Batch Data Ingestion
- Streaming Data Ingestion
- Data Processing
- Interactive Analytics
- Data Warehousing
- Data Sharing
- Data Federation
- Predictive Analytics
- Generative AI
- Operational Analytics
- Business Intelligence
- Data Governance
- Data Mesh
- Performant and Cost-effective Data Platform
- Automate, Operationalize and Monetize
Behram Irani is currently a technology leader with Amazon Web Services (AWS) specializing in data, analytics and AI/ML. He has spent over 18 years in the tech industry helping organizations, from start-ups to large-scale enterprises, modernize their data platforms. In the last 6 years working at AWS, Behram has been a thought leader in the data, analytics and AI/ML space; publishing multiple papers and leading the digital transformation efforts for many organizations across the globe. Behram has completed his Bachelor of Engineering in Computer Science from the University of Pune and has an MBA degree from the University of Florida.
