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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

Implementing a Data Vault

So far in this book, design chapters were followed by provision and implement chapters. A Data Vault data warehouse, however, is a relational database. You can implement a Data Vault using either a SQL database or a Synapse Analytics dedicated SQL pool. The choice is largely economical. The total size of the Data Vault will matter. You need to estimate the total size. Once you know the tables and the data types of the columns, you can calculate the size by estimating the number of rows. You then need to know something about the usage and the performance you need. Size and performance together determine whether a SQL database will do the job or whether you need a Synapse SQL pool. In both cases, you can use the skills learned in earlier chapters to implement the Data Vault.

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