Free shipping on orders over $99
Azure Data Engineering Cookbook

Azure Data Engineering Cookbook

Get well versed in various data engineering techniques in Azure using this recipe-based guide

by Nagaraj Venkatesan and Ahmad Osama
Paperback
Publication Date: 26/09/2022

Share This Book:

  $75.89
or 4 easy payments of $18.97 with
afterpay
Nearly 80 recipes to help you collect and transform data from multiple sources into a single data source, making it way easier to perform analytics on the data

Key Features

Build data pipelines from scratch and find solutions to common data engineering problems
Learn how to work with Azure Data Factory, Data Lake, Databricks, and Synapse Analytics
Monitor and maintain your data engineering pipelines using Log Analytics, Azure Monitor, and Azure Purview

Book DescriptionThe 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.

What you will learn

Process data using Azure Databricks and Azure Synapse Analytics
Perform data transformation using Azure Synapse data flows
Perform common administrative tasks in Azure SQL Database
Build effective Synapse SQL pools which can be consumed by Power BI
Monitor Synapse SQL and Spark pools using Log Analytics
Track data lineage using Microsoft Purview integration with pipelines

Who this book is forThis book is for data engineers, data architects, database administrators, and data professionals who want to get well versed with the Azure data services for building data pipelines. Basic understanding of cloud and data engineering concepts will help in getting the most out of this book.
ISBN:
9781803246789
9781803246789
Category:
Data warehousing
Format:
Paperback
Publication Date:
26-09-2022
Publisher:
Packt Publishing Limited
Country of origin:
United Kingdom
Edition:
2nd Edition
Pages:
608
Dimensions (mm):
93x75mm

This title is in stock with our Australian supplier and should arrive at our Sydney warehouse within 2 - 3 weeks of you placing an order.

Once received into our warehouse we will despatch it to you with a Shipping Notification which includes online tracking.

Please check the estimated delivery times below for your region, for after your order is despatched from our warehouse:

ACT Metro: 2 working days
NSW Metro: 2 working days
NSW Rural: 2-3 working days
NSW Remote: 2-5 working days
NT Metro: 3-6 working days
NT Remote: 4-10 working days
QLD Metro: 2-4 working days
QLD Rural: 2-5 working days
QLD Remote: 2-7 working days
SA Metro: 2-5 working days
SA Rural: 3-6 working days
SA Remote: 3-7 working days
TAS Metro: 3-6 working days
TAS Rural: 3-6 working days
VIC Metro: 2-3 working days
VIC Rural: 2-4 working days
VIC Remote: 2-5 working days
WA Metro: 3-6 working days
WA Rural: 4-8 working days
WA Remote: 4-12 working days

Reviews

Be the first to review Azure Data Engineering Cookbook.