Book Image

Data Modeling for Azure Data Services

By : Peter ter Braake
Book Image

Data Modeling for Azure Data Services

By: Peter ter 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)
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

Understanding big data

What is big data?

Well, here's one practical definition:

You have big data when you need to innovate to do with your data what you need to do.

This means that if your biggest database is an Excel sheet where you have reached the limit of 1 million rows, you have big data. In this case, you need to use another application, possibly on other hardware, to keep working with that data.

This definition is more of a joke than a real definition. However, there is a kernel of truth in there, as well as a warning. When you want to do with your data what companies have been doing with their data for years, you are probably better off using a relational database. Some companies implement big data solutions because they feel they have to. They worry that if they don't, the competition will. But without a solid business case for big data, you are better off using a well-known solution on proven technology. The big data world is moving very rapidly. There...