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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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Loading data into a Big Data Cluster

In this recipe, you are going to design an SSIS package used to load data into a database hosted on the remote SQL Server instance.

The SSIS package contains two control flows:

One extracts key information from the line-of-business database, and loads it into a Staging database hosted in Azure
The other simulates a process that delivers data from a different source (for instance, managed by another department in your organization, or another organization altogether) and loads it into your Big Data Cluster that is also hosted in Azure

The objective of this SSIS package is to make the necessary data available at the remote location for further processing. The SSIS package that you are going to design in the last recipe of this chapter, entitled Extracting data from a Big Data Cluster, depends on the data made available by the package designed in this recipe.

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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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