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Data Modeling for Azure Data Services
Data Modeling for Azure Data Services

Data Modeling for Azure Data Services: Implement professional data design and structures in Azure

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Key benefits

  • Design a cost-effective, performant, and scalable database in Azure
  • Choose and implement the most suitable design for a database
  • Discover how your database can scale with growing data volumes, concurrent users, and query complexity

Description

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.

Who is this book for?

This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

What you will learn

  • Model relational database using normalization, dimensional, or Data Vault modeling
  • Provision and implement Azure SQL DB and Azure Synapse SQL Pools
  • Discover how to model a Data Lake and implement it using Azure Storage
  • Model a NoSQL database and provision and implement an Azure Cosmos DB
  • Use Azure Data Factory to implement ETL/ELT processes
  • Create a star schema model using dimensional modeling

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 30, 2021
Length: 428 pages
Edition : 1st
Language : English
ISBN-13 : 9781801077347
Vendor :
Microsoft
Category :
Languages :
Concepts :
Tools :

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Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
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Product Details

Publication date : Jul 30, 2021
Length: 428 pages
Edition : 1st
Language : English
ISBN-13 : 9781801077347
Vendor :
Microsoft
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total $ 158.97
Data Modeling for Azure Data Services
$54.99
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Customer reviews

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(16 Ratings)
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4 star 25%
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JT Aug 03, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Captured details on data modeling on azure data services.
Amazon Verified review Amazon
Gary J Mersy Apr 12, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book covered logical modeling and transitions to SQL and No SQL for Azure. And, covered data warehouse and data lake with dimensional and data vaults. Definitely covered the gamut. Well done.
Amazon Verified review Amazon
Matt Gordon Nov 01, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Reading through the table of contents, you realize the author is trying to get a lot of information into your hands through the course of the book. While it seems like a lot (and it is), this book does an excellent job of laying the foundation for not only what a database is, but what your relational database options are in the cloud. It builds on that to walking the reader through a solid introduction to the basics of the various database platforms on Azure and how the basics get done on those platforms. This is a really nice introduction to databases, data modeling, and working with those databases in Azure. I highly recommend it for folks new to a data career or wanting to give themselves a broader base to their data career.
Amazon Verified review Amazon
B. Self Aug 16, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a very comprehensive introduction into the Azure Data Engineering landscape starting out with an introduction into the background of how databases came to be all the way through to implementing best practices in the Azure Landscape including both SQL and NoSQL based data implementations.This book would be a very good guide for both seasoned and non-seasoned Data Engineers, both as an introduction and and as reference material for those that are longer in the tooth.Peter has a very good writing style which makes it easy to understand even the most complex of ideas and will definitely be keeping an eye out for any new books he writes on the subject.
Amazon Verified review Amazon
Niklas Fehrenbach Aug 06, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Note: I have received an advanced copy for free from publisher.The book “Data Modeling for Azure Data Services” is a perfect read for professionals and interested individuals who would like to learn more about fundamental database designs and concepts. Starting with traditional relational systems (OLTP), the book also covers NoSQL and OLAP technologies that are extensively explained in the context of Azure PaaS (Azure SQL DB, Azure Cosmos DB, Azure Data Lake and Azure Synapse SQL Pool). In the final chapter the author introduces Microsoft’s ETL Tool, the Azure Data Factory, which can be used to load, visually transform and orchestrate the data in an Azure Analytics architecture.The theoretical content is complemented by exercises and code snippets that are also available in Github. This opportunity to implement the explained concepts makes the book truly valuable in practice as well – especially when new to Azure, but also when optimizing and challenging existing designs.
Amazon Verified review Amazon
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