Azure Data Factory is a fully managed cloud ETL service that allows you to create data integration solutions in the cloud.
With ADF, you can quickly ingest data from disparate sources, process and transform it, and publish the resulting dataset to data warehouses and lakes.
Some key features of ADF:
- Drag-and-drop interface to build pipelines fast without coding
- Connectors for 100+ data sources like SQL Server, Oracle, Blob Storage, etc.
- Powerful data transformation logic with mapping data flows
- Scheduling and monitoring built-in pipelines
- Integration with other Azure ETL services like Databricks and Synapse Analytics
Now let’s look at how easy it is to build an ETL pipeline with ADF using a hands-on example.
Walkthrough: Building a Pipeline
I’m going to build a pipeline that copies data from an on-prem SQL Server to Azure Blob Storage. Here are the steps:
Step 1: Create a data factory
- Go to the Azure portal and create a new resource. Search for “data factory” and create one.
- Give your data factory a name like “MyETLPipeline.” Choose the subscription, resource group, and location.
Step 2: Create linked services
Linked services define the connection to data sources. Create two linked services via the Author & Monitor hub in ADF:
- OnPremSQLDB: Linked service for source SQL Server database. Specify the connection string.
- AzureBlobStorage: Linked service for target blob storage. Specify the storage account name and key.
Step 3: Create input and output datasets
Datasets represent data structures/schema. Create two datasets:
- SrcData: Point to SQL Server table as source.
- SinkData: Point to the Blob container as the sink. Specify the format as Parquet.
Step 4: Create the pipeline
- In the Integrate hub, click Pipeline and create a new pipeline.
- Drag-drop the Copy activity onto the pipeline canvas.
- Configure the Copy activity to use the source and sink datasets.
- Trigger the pipeline on a schedule or trigger.
That’s it! Your first ETL pipeline is now ready. You can monitor the pipeline runs and data movement in the Monitor hub.
Key Takeaways
- Azure Data Factory provides a code-free UI to build data pipelines fast.
- You link data sources as linked services, datasets for schema, and design pipelines with activities like Copy and Data Flow.
- ADF handles executing the pipelines on schedule and monitoring runs.
- With a few clicks, you can build robust ETL processes to ingest data from disparate sources to your data warehouse.
Azure Data Factory is the perfect cloud ETL option if you want to get started fast without coding. Its user-friendly interface, combined with a powerful backend, makes ADF a go-to choice for your data integration workloads.
