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Data Lakehouse in Action

You're reading from   Data Lakehouse in Action Architecting a modern and scalable data analytics platform

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801815932
Length 206 pages
Edition 1st Edition
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Author (1):
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Pradeep Menon Pradeep Menon
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Pradeep Menon
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Table of Contents (14) Chapters Close

Preface 1. PART 1: Architectural Patterns for Analytics
2. Chapter 1: Introducing the Evolution of Data Analytics Patterns FREE CHAPTER 3. Chapter 2: The Data Lakehouse Architecture Overview 4. PART 2: Data Lakehouse Component Deep Dive
5. Chapter 3: Ingesting and Processing Data in a Data Lakehouse 6. Chapter 4: Storing and Serving Data in a Data Lakehouse 7. Chapter 5: Deriving Insights from a Data Lakehouse 8. Chapter 6: Applying Data Governance in the Data Lakehouse 9. Chapter 7: Applying Data Security in a Data Lakehouse 10. PART 3: Implementing and Governing a Data Lakehouse
11. Chapter 8: Implementing a Data Lakehouse on Microsoft Azure 12. Chapter 9: Scaling the Data Lakehouse Architecture 13. Other Books You May Enjoy

The three components of the data governance layer

Recall that in Chapter 2, Data Lakehouse Architecture Overview, we briefly discussed the three components of the data governance layer. The following figure provides a recap of the three components of data governance:

Figure 6.4 – The three components of the data governance layer

Figure 6.4 – The three components of the data governance layer

The three components of data governance are as follows:

  • Data Governance Policy Management: The first component is not a technology component; it is a set of data policies and standards. The data policy is a set of statements describing the rules of controlling the standards, security, integrity, quality, and data usage in the Data Lakehouse.
  • Data Curation and Cataloging Service: Data cataloging is the process of organizing an inventory of data so that it can be easily identified. This service ensures that all the source data, the data in the data lake, the data in the data warehouse, the data processing pipelines...
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