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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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Processing and querying very large datasets

Synapse SQL uses distributed query processing, the data movement service, and scale-out architecture, leveraging the advantages of the scalability and flexibility of compute and storage. Data transformation is not required prior to loading it to Synapse SQL. We need to use the built-in massively parallel processing capabilities of Synapse, load data in parallel, and then perform the transformation.

Loading data using PolyBase external tables and COPY SQL statements is considered one of the fastest, most reliable, and scalable ways of loading data. We can use external data stored in ADLS and Azure Blob storage, and load data using the COPY statement. This data is then loaded to production tables and exposed as views, which creates a query view for the client applications to derive meaningful business insights.

Getting ready

We will be performing a series of steps in order to extract, load, and create a materialized view of data for...

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