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Labs

Developing a Pipeline in Azure Data Factory

Azure Data Factory is a core service for any Azure cloud project. It is an orchestration service responsible for the movement and automation of data into and throughout the Azure cloud. In this lab, we will learn how to connect data sources and create a data pipeline that will move data in Azure. In this scenario, you work for a company selling various items online all around the United States. You have been asked to research a way to combine sales data with other data sources, such as parking lot information to highlight potential new brick-and-mortar stores. In order to do this, you are going to provide a presentation on leveraging cloud services (specifically Data Factory) to automate this research. https://docs.microsoft.com/en-us/learn/modules/data-integration-azure-data-factory/ https://docs.microsoft.com/en-us/learn/modules/orchestrate-data-movement-transformation-azure-data-factory/ https://docs.microsoft.com/en-us/learn/modules/receive-data-with-azure-data-share-transforming-with-azure-data-factory/ https://docs.microsoft.com/en-us/learn/modules/create-production-workloads-azure-databricks-azure-data-factory/

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Lab platform
Lab Info
Level
Beginner
Last updated
Sep 23, 2025
Duration
1h 0m

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Table of Contents
  1. Challenge

    Prepare the Environment

    Provision the following:

    • A Data Factory instance
      • West US 2 region, V2, configure Git later
    • SQL databases
      • Create a server in East US
      • Ensure it's set to 5 (Basic) DTUs at 2 GB
    • A storage account
      • West US 2, Standard Performance, Storage V2, RA-GRS
      • Create 2 containers (raw, curated)
  2. Challenge

    Create and Connect Datasets

    Connect the SQL database (SalesLT.Address table) and storage account from the previous step. Then, download a CSV file and add it to the blob storage account for later use.

  3. Challenge

    Create the Copy Steps of Our Pipeline

    Create a copy step to pull the SalesLT.Address data from the SQL database that will output to the storage account blob container. Then, validate and execute this pipeline.

  4. Challenge

    Use Data Flow to Combine Data from our Copied File and CSV File

    Use Data Flow to add data from the newly copied file to the CSV file. This new data will then be output to a new blob file in the curated container.

  5. Challenge

    Publish the Pipeline

    Publish the completed pipeline.

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