Book Image

Azure Synapse Analytics Cookbook

By : Gaurav Agarwal, Meenakshi Muralidharan
Book Image

Azure Synapse Analytics Cookbook

By: Gaurav Agarwal, Meenakshi 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)

Optimizing analytics with dedicated SQL pool and working on data distribution

In this section, we will understand the in-depth details of dedicated SQL pool for optimizing analytics on a larger dataset. We need to understand the basics of column storage; know when to use round robin, hash distribution, and replicated data distributions; know when to partition a table and check for data skew and space usage; know the best practices and how to effectively use workload management for dedicated SQL pool.

Understanding columnstore storage details

A columnar store is logically organized as a table with rows and columns. It is physically stored in a column-wise data format. Generally, a rowgroup (group of rows) is compressed in columnar store format. A rowgroup consists of the maximum number of rows per rowgroup. The columnstore index slices the table into rowgroups and then compresses the rowgroups column-wise.

A clustered columnstore index is the primary storage for the entire...