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Data Lakehouse in Action

By Pradeep Menon
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  1. Free Chapter
    Chapter 1: Introducing the Evolution of Data Analytics Patterns
About this book
The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner.
Publication date:
March 2022
Publisher
Packt
Pages
206
ISBN
9781801815932

 

PART 1: Architectural Patterns for Analytics

This section describes the evolution of data architecture patterns for analytics. It addresses the challenges posed by different architectural patterns and establishes a new paradigm, that is, the data lakehouse. An overview of the data lakehouse architecture is also provided, which includes coverage of the principles that govern the target architecture, the components that form the data lakehouse architecture, the rationale and need for those components, and the architectural principles adopted to make a data lake scalable and robust.

This section comprises the following chapters:

  • Chapter 1, Introducing the Evolution of Data Analytics Patterns
  • Chapter 2, The Data Lakehouse Architecture Overview
About the Author
  • Pradeep Menon

    Pradeep Menon is a seasoned data analytics professional with more than 18 years of experience in data and AI. Pradeep can balance business and technical aspects of any engagement and cross-pollinate complex concepts across many industries and scenarios. Currently, Pradeep works as a data and AI strategist at Microsoft. In this role, he is responsible for driving big data and AI adoption for Microsoft’s strategic customers across Asia. Pradeep is also a distinguished speaker and blogger and has given numerous keynotes on cloud technologies, data, and AI.

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Data Lakehouse in Action
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