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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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Michelle Gutzait Michelle Gutzait
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Michelle Gutzait
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Toc

Databricks notebook


We are now ready to consume and transform data from the Sales.txt file we created in the previous section. We'll go back to the Databricks workspace and create a new notebook. The easiest way to achieve it is to use a template. As shown in the following screenshot, we select the Data icon in the toolbar at the left of our workspace. We go to Tables | Spark Data Sources | Azure Blob Storage. Click on Create Table in Notebook to create the new notebook:

The notebook opens, with lots of sections. We'll first rename it, right-click on the notebook name and select Rename.

Enter ADFV2Notebook and click on Rename to rename it.

We'll now move it to the ADFCalls folder. Right-click again on the newly renamed notebook and select Move from the submenu, as shown next:

The following dialog box appears. Select the folder ADFCalls and click on Select to move the notebook to its desired location:

Now that the notebook is named and located properly, we'll modify its content.

A notebook is used...

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