Developing a Pipeline in Azure Data Factory

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Cloud

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/

Get started Contact sales

Lab Info

Level

Beginner

Last updated

Sep 23, 2025

Duration

1h 0m

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)
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.
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.
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.
Challenge

Publish the Pipeline

Publish the completed pipeline.

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