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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.

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

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Amazon verified reviews

JT Aug 03, 2021

Captured details on data modeling on azure data services.

Amazon Verified review

Gary J Mersy Apr 12, 2022

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.

Matt Gordon Nov 01, 2021

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.

B. Self Aug 16, 2021

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.

Niklas Fehrenbach Aug 06, 2021

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.

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

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