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Hands-On Data Warehousing with Azure Data Factory

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

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781789137620
Length 284 pages
Edition 1st Edition
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Authors (3):
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Christian Cote Christian Cote
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Christian Cote
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Michelle Gutzait Michelle Gutzait
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Michelle Gutzait
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Toc

Different types of BI


In this section, we will discuss various types of BI depending on the use cases.

Self-service – personal

This is the type of BI or reports that users will work upon themselves. In this scenario, they use Power BI for desktop to connect to the data sources they want to, whether they are in the data warehouse or anywhere else on the cloud, such as Twitter feeds, data lakes, Spark, and so on.

Most of these sources require that users import data in the Power BI data model to their local machine. If the data source contains a large amount of data, this can consume a lot of resources. But in this mode, data can be altered, in the sense that the source data can be merged or transformed. No live connection is needed to connect to the data as it is imported to Power BI's underlying model. This model is meant to allow users to explore their data and modify it to suit their needs better. They have almost complete control over it.

If the data source is an SQL Server relational database...

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