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ETL with Azure Cookbook

You're reading from ETL with Azure Cookbook Practical recipes for building modern ETL solutions to load and transform data from any source

Product type Paperback

Published in Sep 2020

Publisher Packt

ISBN-13 9781800203310

Length 446 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Databases

Authors (3):

Christian Cote

Matija Lah

Madina Saitakhmetova

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Getting Started with Azure and SSIS 2019

2. Chapter 2: Introducing ETL FREE CHAPTER

3. Chapter 3: Creating and Using SQL Server 2019 Big Data Clusters

4. Chapter 4: Azure Data Integration

5. Chapter 5: Extending SSIS with Custom Tasks and Transformations

6. Chapter 6: Azure Data Factory

7. Chapter 7: Azure Databricks

8. Chapter 8: SSIS Migration Strategies

9. Chapter 9: Profiling data in Azure

10. Chapter 10: Manage SSIS and Azure Data Factory with Biml

11. Other Books You May Enjoy

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Creating an on-demand Azure HDInsight cluster

So far, we have installed the Azure Feature Pack in SSIS and created a storage account. It is now time to create a compute service in Azure so that we can manipulate some data.

An HDInsight cluster is what we call a compute resource in Azure. It is essentially a Hortonworks (now Cloudera) service available in Azure. It is composed of Linux virtual machines that have Apache Hadoop or Spark installed on them. Hadoop has been around for more than a decade now and it was the first big data compute resource available. Hadoop writes (stages) the data to disk at almost all the stages of a program's execution. Spark is a newer technology. Instead of staging data on disks, it uses memory while a program executes. It's therefore much faster than Hadoop.

We will use Hadoop clusters in this chapter because SSIS uses this type of cluster. HDInsight clusters can be very expensive if we create them manually and leave them running continuously...

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Authors (3)

Cote

Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).

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Saitakhmetova

Saitakhmetova

Madina Saitakhmetova is a developer specializing in BI. She has been in IT for 15 years, working first with Microsoft SQL, .Net Framework, and then Microsoft BI, BIML and Azure. Her adventure with Microsoft BI began with Analysis Services and SSIS, but she is leaning towards ETL development, both on premises and in the cloud, in later years. Finding patterns, automating processes and making BI team work more efficient are challenges that drive her. During past few years, BIML has become an important part of her work, increasing efficiency and quality

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Lah

Lah

Matija Lah has more than 18 years of experience working with Microsoft SQL Server, mostly from architecting data-centric solutions in the legal domain. His contributions to the SQL Server community have led to him being awarded the MVP Professional award (Data Platform) between 2007 and 2017/2018. He spends most of his time on projects involving advanced information management and natural language processing, but often finds time to speak at events related to Microsoft SQL Server where he loves to share his experience with the SQL Server platform.

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