How to Create Synapse Pipeline to Copy Data from CSV to Dedicated SQL Pool from Scratch | Azure Synapse Analytics Tutorial

Create Synapse Pipeline to Copy CSV Data to Dedicated SQL Pool

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.