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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

Context of an ERD

ERDs are used in many different ways. We've used them here as an aid in database modeling. They can be a first, high-level step to get an impression of what we are dealing with. We define the scope and create a rough first draft of what our database might look like.

Application developers who write queries against databases need to know the database. What information is stored where? An ERD is a handy tool to get the needed insight. You see all the tables and which tables are related. When you add keys to the ERD (name an entity as we did plus add the primary and foreign keys in the entity's rectangle), you also know how tables are related. You can even add all the columns, as in Figure 2.1 at the start of this chapter. This ERD contains all the detailed information needed to start implementing the database.

There are multiple steps to be taken in between what we have created so far and the ERD of Figure 2.1. In Chapter 3, Normalizing Data, we are...

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