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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 1. PART 1: Architectural Patterns for Analytics
2. Chapter 1: Introducing the Evolution of Data Analytics Patterns 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 logical data lakehouse architecture

We have discussed a data lakehouse system context. Let's now get into developing a logical data lakehouse architecture. A logical architecture focuses on components that integrate to satisfy specific functional requirements (FRs) and non-functional requirements (NFRs). It is abstracted to a level that is technology-agnostic and focuses on component functionality. A logical architecture focuses on two kinds of requirements, as follows:

  • An FR is a requirement that fulfills a specific business or domain-driven behavior. These kinds of requirements are driven by the tasks and the needs of a particular business function.
  • An NFR is a requirement that specifies criteria that need to be fulfilled for the system to be helpful in that specific context. For example, a typical NFR includes the time a particular query is expected to complete, a requirement for data encryption, and so on.

A well-architected system ensures that...

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