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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook - Second Edition

By : Nagaraj Venkatesan, Ahmad Osama
4.6 (13)
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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook

4.6 (13)
By: Nagaraj Venkatesan, Ahmad Osama

Overview of this book

The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.
Table of Contents (16 chapters)
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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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83
Tech Concepts
36
Programming languages
73
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Azure Data Engineering Cookbook
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