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)

Chapter 3: Processing Data Optimally across Multiple Nodes

In this chapter, we will cover the Synapse SQL architecture components that are required for running data transformation pipelines and leverage the scale-out capabilities to distribute computational data processing and transformation across multiple nodes. Synapse SQL architecture is designed in such a way that the compute is totally separated from storage and, as needed, the compute can be scaled independently of the data. Since compute and data are separated, the queries handled by compute enable massively parallel processing, performance, and greater speed in retrieving the data.

We will cover the following recipes:

  • Working with the resource consumption model of Synapse SQL
  • Optimizing analytics with dedicated SQL pool and working on data distribution
  • Working with serverless SQL pool
  • Processing and querying very large datasets
  • Script for statistics in Synapse SQL