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Azure Data Engineering Cookbook

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

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803246789
Length 608 pages
Edition 2nd Edition
Languages
Tools
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Authors (3):
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Ahmad Osama Ahmad Osama
Author Profile Icon Ahmad Osama
Ahmad Osama
Nagaraj Venkatesan Nagaraj Venkatesan
Author Profile Icon Nagaraj Venkatesan
Nagaraj Venkatesan
Luca Zanna Luca Zanna
Author Profile Icon Luca Zanna
Luca Zanna
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Toc

Table of Contents (16) Chapters Close

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 15. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

active geo-replication

configuring 204, 205

implementing, for Azure SQL database with PowerShell 200

manual failover, performing to secondary database 202, 203

readable secondary, creating 200, 201

removing 204

use cases 200

advanced workload management

workload groups, creating 436-442

alert

creating, to monitor Azure storage account 45-54

Archive tier 16

Artificial Intelligence (AI) 247

Atomicity, Consistency, Isolation, and Durability (ACID) 292

auto-failover group

creating 205, 206, 207

implementing, for Azure SQL database with PowerShell 205

performing, to secondary server 208, 209

working 210

automatic tuning features

CREATE INDEX 241

DROP INDEX 241

FORCE PLAN 241

AutoResolveIntegrationRuntime 99

Azure blob

access...

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