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You're reading from Hands-On Data Warehousing with Azure Data Factory ETL techniques to load and transform data from various sources, both on-premises and on cloud

Product type Paperback

Published in May 2018

Publisher Packt

ISBN-13 9781789137620

Length 284 pages

Edition 1st Edition

Languages

SQL

Tools

Azure

Concepts

Big Data

Authors (3):

Christian Cote

Giuseppe Ciaburro

Michelle Gutzait

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Table of Contents (8) Chapters

Preface

1. The Modern Data Warehouse

2. Getting Started with Our First Data Factory FREE CHAPTER

3. SSIS Lift and Shift

4. Azure Data Lake

5. Machine Learning on the Cloud

6. Introduction to Azure Databricks

7. Reporting on the Modern Data Warehouse

Summary

In this chapter, we created our factory with a pipeline that copies data from an Azure SQL database to an Azure storage account. The following chapters will dig more into the various services available in Azure as well as how we can integrate an existing SSIS solution into the factory.

You have been reading a chapter from

Hands-On Data Warehousing with Azure Data Factory

Published in: May 2018

Publisher: Packt

ISBN-13: 9781789137620

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Authors (3)

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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Michelle Gutzait

Michelle Gutzait has been in IT for 30 years as a developer, business analyst, and database

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Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

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