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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

Developing a system context for a data lakehouse

A system context diagram shows different entities that interact with a system. In the following case, the system is a data lakehouse:

Figure 2.1 – Data lakehouse system context diagram

The preceding diagram shows key entities (systems or actors) that interact with the data lakehouse. The interaction with the data lakehouse has two parts, as outlined here:

  • Data providers: Systems or actors that provide data to the data lakehouse
  • Data consumers: Systems or actors that consume data from the data lakehouse

Let's examine these entities in detail.

Data providers

Data providers are any system or actor that ingests data into the data lakehouse. Any system that generates data is a potential data provider. A few typical data providers are listed here:

  • Operational systems: Any system that generates data is a potential data provider. Typically, online transaction processing ...
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