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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

Integrating separate results

We analyzed two different reports in the two previous sections of this chapter. Both reports provide information on the same project organization and show data coming from the same database. The results of the independently analyzed reports need to be integrated into a single database schema.

During integration, we merge the result of normalizing the information requirements. We need to pay attention to the following:

  • Tables that describe the same entity
  • Homonyms and synonyms
  • Process data

Tables that are the same

An entity (a table) is defined by its key. So, we first look for tables with the same key. We can merge these tables.

Both in Figure 3.7 and in Figure 3.15, we see a table called Project. The fact that we chose the same name is irrelevant, just a coincidence. The fact that both tables have the same key, ProjectNumber, means that they are actually the same table. You merge them by creating a table that contains all...

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