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Data Modeling for Azure Data Services

You're reading from   Data Modeling for Azure Data Services Implement professional data design and structures in Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077347
Length 428 pages
Edition 1st Edition
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Author (1):
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Peter ter Braake Peter ter Braake
Author Profile Icon Peter ter Braake
Peter ter Braake
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Table of Contents (16) Chapters Close

Preface 1. Section 1 – Operational/OLTP Databases
2. Chapter 1: Introduction to Databases FREE CHAPTER 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

Chapter 9: Data Vault Modeling

In Chapter 7, Dimensional Modeling, you learned how to create a star schema database. In Chapter 8, Provisioning and Implementing an Azure Synapse SQL Pool, you implemented a star schema. The goal was to optimize the database for analysis and reporting.

Demands and regulations change over time, meaning that the way we use data also changes over time. These changes the way we use data for us to implement changes in the star schema designs we create. To create a stable data platform, we implement a layer in between the operational databases that we learned about in chapters 3 to 6, and the dimensionally modeled databases that we learned about in Chapter 7, Dimensional Modeling, and Chapter 8, Provisioning and Implementing an Azure Synapse SQL Pool. This layer should be optimized for the long-term, flexible storage of historical data. When data here means relational data, creating a data vault data warehouse is a good option. That is what this chapter...

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