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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

Other NoSQL databases

Azure Cosmos DB allows us to choose between five different APIs when programming against Cosmos DB. All APIs can be used using multiple programming languages. The five APIs are the following:

  • SQL
  • MongoDB
  • Gremlin
  • Cassandra
  • Table

The preferred API to use is the SQL API. This allows a programmer to use SQL queries to query the database. This leverages the power of the SQL language and the SQL experience that a lot of developers have. We will see some examples of using SQL in Cosmos DB in Chapter 6, Provision and Implement an Azure Cosmos DB Instance.

The other four APIs all have the purpose of making migrations from on-premises NoSQL implementations to Azure Cosmos DB easier. We already mentioned the MongoDB API and the Table API. Use the Table API when you have existing code that works against a MongoDB document database. Use the Table API when you are migrating an Azure tables database to Cosmos DB.

Gremlin

The Gremlin API...

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