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Data Modeling for Azure Data Services

You're reading from  Data Modeling for Azure Data Services

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077347
Pages 428 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Peter ter Braake Peter ter Braake
Profile icon Peter ter Braake
Toc

Table of Contents (16) Chapters close

Preface 1. Section 1 – Operational/OLTP Databases
2. Chapter 1: Introduction to Databases 3. Chapter 2: Entity Analysis 4. Chapter 3: Normalizing Data 5. Chapter 4: Provisioning and Implementing an Azure SQL DB 6. Chapter 5: Designing a NoSQL Database 7. Chapter 6: Provisioning and Implementing an Azure Cosmos DB Database 8. Section 2 – Analytics with a Data Lake and Data Warehouse
9. Chapter 7: Dimensional Modeling 10. Chapter 8: Provisioning and Implementing an Azure Synapse SQL Pool 11. Chapter 9: Data Vault Modeling 12. Chapter 10: Designing and Implementing a Data Lake Using Azure Storage 13. Section 3 – ETL with Azure Data Factory
14. Chapter 11: Implementing ETL Using Azure Data Factory 15. Other Books You May Enjoy

Modeling a data lake

A data lake is, in essence, nothing more than a limitless hard drive that we use to store files. Everyone knows that if you do not carefully consider a folder structure to use on your personal computer, you will end up with a mess and it will become almost impossible to find your files. It is no different for your data lake. Although we cannot speak of data modeling when designing a data lake, creating a structure is really important for a successful implementation. That is even more true when the data in the data lake is made available to end users, such as data analysts working with Power BI or data scientists working with Python notebooks.

When creating a folder structure, you need to take the following things into account:

  • The source of the data
  • The functional meaning of the data
  • Security: Who may or may not need to have access to the data?
  • Who and which applications will use the data?
  • Is the data stored permanently or temporarily...
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