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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

Creating multiple storage accounts

You can provision as many storage accounts as you like. There are four high-level considerations when it comes to choosing how many storage accounts you need:

  • DTAP
  • Data diversity
  • Cost sensitivity
  • Management overhead

Let's look at each of them in a little more detail.

Considering DTAP

DTAP stands for development, testing, acceptance, and production. Each stands for a separate environment used in a separate stage in the creation of, and working with, a data lake. You probably need to create some code to move data from the source systems into the data lake and then through the different data lake zones. This is a work in progress that should be separated from business processes working with data already in the data lake. You will most likely want to have small test datasets to create the logic and workflow to save development time.

After new software is written, it must be tested. You may have separate datasets...

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