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Data Modeling for Azure Data Services

Data Modeling for Azure Data Services

By : Braake
4.8 (16)
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Data Modeling for Azure Data Services

Data Modeling for Azure Data Services

4.8 (16)
By: Braake

Overview of this book

Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution.
Table of Contents (16 chapters)
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1
Section 1 – Operational/OLTP Databases
8
Section 2 – Analytics with a Data Lake and Data Warehouse
13
Section 3 – ETL with Azure Data Factory

Designing a Data Vault structure

Let's start with the modeling process. There are two ways to design a Data Vault, both using the same general approach. This approach consists of the following steps:

  1. Identify the business keys, the natural entities involved in the process you try to model. This creates the Hub tables.
  2. Identify the relationships between the created Hubs. This creates the Link tables.
  3. Identify the descriptive information to store in the data warehouse. Create Satellites to store this data.
  4. Possibly re-group the descriptive columns based on type, rate of change, or source system and create Satellite tables accordingly.

There are two starting points you can choose to start modeling a Data Vault structure. These are as follows:

  • Translate a normalized database design into Hubs, Links, and Satellites.
  • Determine the entities by analyzing the business processes to model.

The easiest way is to take an existing normalized source...

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