How to Create Synapse Pipeline to Copy Data from CSV to Dedicated SQL Pool
📘 Overview
In this tutorial, you’ll learn how to build a Synapse pipeline from scratch to copy data from a CSV file in Azure Data Lake Storage Gen2 to a table in a Dedicated SQL Pool. This is a common ETL scenario in modern data warehousing using Azure Synapse Analytics.
🧱 Prerequisites
- A Synapse workspace with a dedicated SQL pool created
- CSV file stored in Azure Data Lake Gen2
- Proper permissions for Linked Services and data access
🛠️ Step-by-Step Instructions
✅ Step 1: Open Synapse Studio
Navigate to your Synapse workspace → Open Synapse Studio✅ Step 2: Create Linked Services
- One for your Azure Data Lake Gen2 (source)
- One for your Dedicated SQL Pool (sink)
✅ Step 3: Create Source Dataset
Choose DelimitedText → CSV
Point to the container and folder where your CSV file is stored
Enable header row, set column delimiter, and schema if needed✅ Step 4: Create Sink Dataset
Choose Azure Synapse Analytics
Select or define the table in your dedicated SQL pool✅ Step 5: Create the Pipeline
1. Go to the Integrate tab
2. Click + > Pipeline
3. Add a Copy Data activity
4. Configure source and sink datasets
5. Map columns (if needed)
6. Debug or trigger manually✅ Step 6: Publish and Monitor
- Click “Publish All” to deploy the pipeline
- Run the pipeline manually or create a trigger
- Monitor progress under the “Monitor” tab
📌 Tips
- Make sure your CSV schema matches the destination table
- Use staging if file size is large for better performance
- Enable logging for troubleshooting
🎯 Use Cases
- Daily ingestion of batch files into SQL Pool
- Building historical data from external systems
- Loading external partner data for analytics
📺 Watch the Full Video Tutorial
📚 Credit: Content created with the help of ChatGPT and Gemini.