You're reading from Azure Data Engineering Cookbook Get well versed in various data engineering techniques in Azure using this recipe-based guide

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781803246789

Length 608 pages

Edition 2nd Edition

Languages

SQL

Tools

Azure

Concepts

Data Engineering

Authors (3):

Ahmad Osama

Nagaraj Venkatesan

Luca Zanna

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Table of Contents (16) Chapters

Preface

1. Chapter 1: Creating and Managing Data in Azure Data Lake

2. Chapter 2: Securing and Monitoring Data in Azure Data Lake FREE CHAPTER

3. Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory

4. Chapter 4: Azure Data Factory Integration Runtime

5. Chapter 5: Configuring and Securing Azure SQL Database

6. Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database

7. Chapter 7: Processing Data Using Azure Databricks

8. Chapter 8: Processing Data Using Azure Synapse Analytics

9. Chapter 9: Transforming Data Using Azure Synapse Dataflows

10. Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool

11. Chapter 11: Monitoring Synapse SQL and Spark Pools

12. Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools

13. Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines

14. Index

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Monitoring and Maintaining Azure Data Engineering Pipelines

12 chapters and 500+ pages into this book should have given you a fair understanding of building Data Factory/Synapse integration pipelines to ingest, process, and store your data. The next key aspect of Azure data engineering is to monitor and maintain the pipelines that you’ve developed.

In this chapter, we will cover the following recipes:

Monitoring Synapse integration pipelines using Log Analytics and workbooks
Tracing SQL queries for Synapse dedicated SQL pools to Synapse integration pipelines
Provisioning a Microsoft Purview account and creating a data catalog
Integrating a Synapse workspace with Microsoft Purview and tracking data lineage
Applying Azure tags using PowerShell to multiple Azure resources

After completing these recipes, you will be familiar with integrating Synapse workspaces with Log Analytics, monitoring Synapse pipeline performance and failures, using labels...