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Azure Synapse Analytics Cookbook

Azure Synapse Analytics Cookbook

By : Agarwal(BLR), Muralidharan
4.7 (18)
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Azure Synapse Analytics Cookbook

Azure Synapse Analytics Cookbook

4.7 (18)
By: Agarwal(BLR), Muralidharan

Overview of this book

As data warehouse management becomes increasingly integral to successful organizations, choosing and running the right solution is more important than ever. Microsoft Azure Synapse is an enterprise-grade, cloud-based data warehousing platform, and this book holds the key to using Synapse to its full potential. If you want the skills and confidence to create a robust enterprise analytical platform, this cookbook is a great place to start. You'll learn and execute enterprise-level deployments on medium-to-large data platforms. Using the step-by-step recipes and accompanying theory covered in this book, you'll understand how to integrate various services with Synapse to make it a robust solution for all your data needs. Whether you're new to Azure Synapse or just getting started, you'll find the instructions you need to solve any problem you may face, including using Azure services for data visualization as well as for artificial intelligence (AI) and machine learning (ML) solutions. By the end of this Azure book, you'll have the skills you need to implement an enterprise-grade analytical platform, enabling your organization to explore and manage heterogeneous data workloads and employ various data integration services to solve real-time industry problems.
Table of Contents (11 chapters)
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Using materialized views to improve performance

In this recipe, you will learn how materialized views can help in solving complex queries that are required for analytical purposes and how you can gain performance. You will learn how to create the materialized view, and when and why to use it in the SQL dedicated pool.

Materialized views are the best option in a large data warehouse, as the data is stored in a pre-processed format, unlike standard views. When you execute a query with a materialized view, it internally keeps processed data within the dedicated SQL pool, just like a physical SQL table.

Getting ready

Before you begin, make sure you have the following:

  • Make sure you have the dedicated SQL pool available in the Synapse workspace.
  • You need to ensure that the table in which you are creating a materialized view has a qualifying column that can participate in the columnstore index. You can refer to this document for a list of datatypes that can participate...

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