- Lab
-
Libraries: If you want this lab, consider one of these libraries.
- Cloud
- Data

Implement a Partition Strategy for Azure Data Factory Pipelines
In this hands-on lab, you will learn how to provision an Azure Data Factory workspace, create pipeline activities to migrate data from an Azure SQL Database into a data lake, and create partitions as you migrate data. The skills learned in this lab are very frequently used by data engineers and data architects. This lab will also touch on critical skills found on the DP-203 exam.

Lab Info
Table of Contents
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Challenge
Prepare the Environment
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Create a Blob Storage account with a Customer Container.
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Create an Azure Data Factory instance in the West US region.
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Create an SQL Database instance and server in the West US region. It should utilize DTU-based basic tier compute. Make sure to choose sample data as the data source.
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Challenge
Create the Data Sources
- Create a dataset that connects to the newly created SQL Database.
- Connect to the
SalesLT.Customer
table.
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Challenge
Create a Data Flow
- Create a data flow with:
- Source linked to
SalesLT.Customer
table. - Sink linked to the newly created data lake (Create the sink as a Parquet file).
- This will require the creation of a sample container in the newly created Azure Storage account.
- Source linked to
- Select and create five hash partitions based upon the most appropriate column.
- Publish all updates.
- Create a data flow with:
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Challenge
Create a Data Pipeline
- Create a pipeline with your newly created Data Flow activity as the only activity.
- Validate and Publish this pipeline.
- Run the pipeline using the Trigger Now option.
- Check that the partitions were created successfully.
About the author
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