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Labs

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.

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Lab platform
Lab Info
Level
Intermediate
Last updated
Sep 23, 2025
Duration
30m

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Table of Contents
  1. Challenge

    Prepare the Environment
    1. Create a Blob Storage account with a Customer Container.

    2. Create an Azure Data Factory instance in the West US region.

    3. 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.

  2. Challenge

    Create the Data Sources
    1. Create a dataset that connects to the newly created SQL Database.
    2. Connect to the SalesLT.Customer table.
  3. Challenge

    Create a Data Flow
    1. Create a data flow with:
      1. Source linked to SalesLT.Customer table.
      2. 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.
    2. Select and create five hash partitions based upon the most appropriate column.
    3. Publish all updates.
  4. Challenge

    Create a Data Pipeline
    1. Create a pipeline with your newly created Data Flow activity as the only activity.
    2. Validate and Publish this pipeline.
    3. Run the pipeline using the Trigger Now option.
    4. Check that the partitions were created successfully.
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