You plan to use an Azure Synapse pipeline to copy CSV files from the branch office, perform complex transformations on their content, and then load them to DB1.

Category : Microsoft Azure Data Engineering | Sub Category : Practice Assessment for Exam DP-203 - Data Engineering on Microsoft Azure | By Prasad Bonam Last updated: 2023-09-10 03:34:03 Viewed : 313

Your company has a branch office that contains a point of sale (POS) system.

You have an Azure subscription that contains a Microsoft SQL Server database named DB1 and an Azure Synapse Analytics workspace.

You plan to use an Azure Synapse pipeline to copy CSV files from the branch office, perform complex transformations on their content, and then load them to DB1.

You need to pass a subset of data to test whether the CSV columns are mapped correctly.

What can you use to perform the test?

Ans :Data Flow Debug

Correct: The Data Flow Debug option is available inside of a data flow activity and allows you to pass a subset of data through the flow, which can be useful to test whether columns are mapped correctly.

Incorrect: Integration runtime is a pipeline concept referring to the compute resources required to execute the pipeline.

Incorrect: A linked service is required when an activity needs or depends on an external service.

Incorrect: Datasets refers to the specific data consumed and produced by activities in a pipeline.

Build a data pipeline in Azure Synapse Analytics - Training | Microsoft Learn

To pass a subset of data to test whether the CSV columns are mapped correctly in an Azure Synapse pipeline, you can use a staging area or a temporary storage location to store the test data before loading it into DB1. Here is a general approach:

1. Create a Staging Area or Temporary Storage:

   • Set up a storage container (e.g., Azure Blob Storage or Azure Data Lake Storage) where you can temporarily store the test CSV files.

2. Generate and Upload Test CSV Files:

   • Create a subset of the CSV files with the data you want to test. Ensure that these files have the same structure (columns) as the actual CSV files.
   • Upload these test CSV files to the staging area or temporary storage.

3. Create a Synapse Pipeline:

   • Create an Azure Synapse pipeline that includes activities to copy the test CSV files from the staging area, perform the required data transformations, and then load them into DB1.

4. Test the Pipeline:

   • Execute the Synapse pipeline using the test CSV files as the source data.
   • Monitor the pipeline run and check for any issues or errors during the data movement and transformation steps.
   • Review the results in DB1 to ensure that the columns are mapped correctly.

5. Cleanup:

   • Once the test is successful, you can delete the test data from the staging area or temporary storage if needed.

By following this approach, you can verify that your pipeline correctly maps the CSV columns and performs the desired transformations without affecting the production data in DB1. This allows you to test and validate your data processing pipeline before using it with the actual data.