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Data Lakehouse in Action

You're reading from  Data Lakehouse in Action

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801815932
Pages 206 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Pradeep Menon Pradeep Menon
Profile icon Pradeep Menon

Table of Contents (14) Chapters

Preface PART 1: Architectural Patterns for Analytics
Chapter 1: Introducing the Evolution of Data Analytics Patterns Chapter 2: The Data Lakehouse Architecture Overview PART 2: Data Lakehouse Component Deep Dive
Chapter 3: Ingesting and Processing Data in a Data Lakehouse Chapter 4: Storing and Serving Data in a Data Lakehouse Chapter 5: Deriving Insights from a Data Lakehouse Chapter 6: Applying Data Governance in the Data Lakehouse Chapter 7: Applying Data Security in a Data Lakehouse PART 3: Implementing and Governing a Data Lakehouse
Chapter 8: Implementing a Data Lakehouse on Microsoft Azure Chapter 9: Scaling the Data Lakehouse Architecture Other Books You May Enjoy

Summary

This chapter was a 30,000-feet overview introduction to a data lakehouse architecture. This chapter started with the system context that established the critical systems and people that generate data for a data lakehouse and consume data from it. Next, we discussed the motivations and use cases for different types of data. Once the section clarified the system context, the chapter introduced the logical architecture of a data lakehouse. Next, the chapter provided a brief overview of the seven layers of a data lakehouse and its components. Finally, the chapter concluded with an elaboration of five sacrosanct architecture principles core to a robust data lakehouse architecture. The chapter lays the architectural foundation for a modern data analytics platform. Now that the stage is set, the subsequent chapters will go deeper into each of the layers and discuss design patterns for each layer.

In the next chapter, we will cover storing data in a data lakehouse.

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