Can we copy SQL Table to Pipe-Separated Files? - Let us see!!
Arpit TyagiTable of contents
- Step 1: Create an instance of Azure Data Factory:
- Step 2: Set up Linked Services:
- Step 3: Create a dataset for both (source-SQL Database and destination-Azure Data Lake):
- Step 4: Build the Data Pipeline with the help of datasets:
- Step 5: Test and Debug the Pipeline:
- Step 6: Verify the Receiver container and the exported file for accuracy and completeness:
Step 1: Create an instance of Azure Data Factory:
Step 2: Set up Linked Services:
Step 3: Create a dataset for both (source-SQL Database and destination-Azure Data Lake):
This is the most important step because we will select the pipe as a delimiter in the options, and Azure Data Factory will handle the rest automatically—
Step 4: Build the Data Pipeline with the help of datasets:
Step 5: Test and Debug the Pipeline:
Step 6: Verify the Receiver container and the exported file for accuracy and completeness:
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Written by
Arpit Tyagi
Arpit Tyagi
Experienced Data Engineer passionate about building and optimizing data infrastructure to fuel powerful insights and decision-making. With a deep understanding of data pipelines, ETL processes, and cloud platforms, I specialize in transforming raw data into clean, structured datasets that empower analytics and machine learning applications. My expertise includes designing scalable architectures, managing large datasets, and ensuring data quality across the entire lifecycle. I thrive on solving complex data challenges using modern tools and technologies like Azure, Tableau, Alteryx, Spark. Through this blog, I aim to share best practices, tutorials, and industry insights to help fellow data engineers and enthusiasts master the art of building data-driven solutions.