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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.

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

Brent Meulebroeck Oct 10, 2021

The first few chapters give an overview of basic database design concepts. As someone who began using SQL as an end user in a business setting prior to being involved in data design & modeling I appreciated these chapters for filling in some gaps for me - I know best practices, but this gave me the 'whys' and context about them. The author also neatly outlines what to consider when moving your data to a cloud service. Advanced users can breeze right past to get to the Azure content.In the middle you get into Azure database specifics - SQL, NoSQL, and how to decide which is appropriate for your use case and how to provision both in the Azure environment. Throughout there are a lot of tips and tricks to help you manage your cost and performance to set everything up correctly from the start, with the ability to scale later on.The second half of the book goes deep into topics around data modeling for analytics (star schema, snowflake, data lake/mart/vaults) and Azure Synapse Analytics and Azure Data Factory. There are exercises throughout to apply your learning immediately, and a companion GitHub repo with all the necessary code and documentation. I also appreciated that the eBook has direct links to Microsoft's own documentation to learn more.I'd recommend this for anyone getting started in database design and data modeling in general, and Azure in particular. I've flagged several topics for upcoming projects, and will recommend this to my peers who are working on Azure deployments.

Amazon Verified review

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.

JT Aug 03, 2021

Captured details on data modeling on azure data services.

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.

Chrisi Aug 03, 2021

This is a great book if you are planning to implement applications and data-backends in Azure. The author not only explains many important data modeling topics such as entity analysis, schema normalization, dimensional modeling, data vault modeling, and more, but also provides practical examples on how to implement these concepts in Azure. RDBMS concepts are implemented using Azure SQL DB.Azure (and many other cloud-based) services require you to learn many new concepts regarding compute, management, failover/replication, scale and billing. The author makes a good job to explain many of these concepts (such as vCores, DTU, Serverless, Hyperscale, Elastic Pools, and more) throughout the book. You definitely need this knowledge as soon as you start your first Azure SQL DB.Another thing I like in particular about this book is that the author also touches on other Azure data services such as Synapse (SQL Pool), Cosmos DB and Azure Data Lake. The author explains how to adjust the data model for these different storage and query engines and provides a great introduction and practical examples. There are many pitfalls when implementing NoSQL data layers or transitioning from an OLTP to an OLAP data model, and reading this book will definitely help to avoid those.The author certainly has deep expertise in the field, and makes a great job explaining complex topics in an understandable way.

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

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