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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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Chapter 1: Choosing the Optimal Method for Loading Data to Synapse

In this chapter, we will cover how to enrich and load data to Azure Synapse using the most optimal method. We will be covering, in detail, different techniques to load data, considering the variety of data source options. We will learn the best practices to be followed for different data loading options, along with unsupported scenarios.

We will cover the following recipes:

  • Choosing a data loading option
  • Achieving parallelism in data loading using PolyBase
  • Moving and transforming using a data flow
  • Adding a trigger to a data flow pipeline
  • Unsupported data loading scenarios
  • Data loading best practices
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