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Azure Synapse Analytics Cookbook

You're reading from Azure Synapse Analytics Cookbook Implement a limitless analytical platform using effective recipes for Azure Synapse

Product type Paperback

Published in Apr 2022

Publisher Packt

ISBN-13 9781803231501

Length 238 pages

Edition 1st Edition

Languages

PySpark

Tools

Azure

Concepts

Data Science

Authors (2):

Gaurav Agarwal(BLR)

Meenakshi Muralidharan

View More author details

Table of Contents (11) Chapters

Preface

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

2. Chapter 2: Creating Robust Data Pipelines and Data Transformation FREE CHAPTER

3. Chapter 3: Processing Data Optimally across Multiple Nodes

4. Chapter 4: Engineering Real-Time Analytics with Azure Synapse Link Using Cosmos DB

5. Chapter 5: Data Transformation and Processing with Synapse Notebooks

6. Chapter 6: Enriching Data Using the Azure ML AutoML Regression Model

7. Chapter 7: Visualizing and Reporting Petabytes of Data

8. Chapter 8: Data Cataloging and Governance

9. Chapter 9: MPP Platform Migration to Synapse

10. Other Books You May Enjoy

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

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Authors (2)

Agarwal(BLR)

Agarwal(BLR)

Gaurav Agarwal is a cloud solution architect at Microsoft India Corp. Ltd, working closely with Microsoft clients on Azure data and AI, Azure ML, big data, IoT, and Power BI. He has extensive experience in architecting and transforming data solutions for the modern cloud, and expertise in building large-scale enterprise data warehouse solutions.

See other products by Agarwal(BLR)

Muralidharan

Muralidharan

Meenakshi Muralidharan leads modern data platforms and is a renowned chief architect for an Indian multinational information technology services and consulting company. She has extensive experience in building large scale data platforms and applications in Microsoft Azure.

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