The practice assessment does not cover SQL, PySpark, KQL, or most of other topics related to ingesting and transforming data. I recently took the DP-700 exam and passed it. In my experience, it was relatively easy, especially compared to the DP-600 exam. However, Microsoft’s official learning materials alone are insufficient for passing the exam, as some questions require a deeper understanding of the subject matter. For additional practice assessments, you may consider using platforms such as certiace.com

@Abdelhak ㅤ "When using your voucher, you will not be able to use it for an exam date attempting to be scheduled for beyond June 21, 2025." https://learn.microsoft.com/en-us/training/topics/event-challenges/ai-skills-fest-challenge-official-rules

@Abdelhak ㅤ good luck with your exam!

@Sumit Sehlot sorry for late answer. I have used this: from notebookutils import fs files_in_path = f"abfss://{fabric_workspace_id}@onelake.dfs.fabric.microsoft.com/{fabric_lakehouse_id}/Files/in" files_archive_path = f"abfss://{fabric_workspace_id}@onelake.dfs.fabric.microsoft.com/{fabric_lakehouse_id}/Files/archive" files = fs.ls(files_in_path) # Filter files based on a pattern (e.g., files starting with "SalesOrder") csv_files = [file.name for file in files if file.name.startswith("SalesOrder")] if csv_files == []: print("No files.") else: for file_name in csv_files: notebookutils.fs.mv(f'{files_in_path}/{file_name}', f'{files_archive_path}/{file_name}', True) Addition to "startswith" you can use also "endswith" and "contains", for Example.

I haven't done it in Fabric, but in Synapse. It should still work, though. You can use a copy activity in your data pipeline or notebook. I have done it both way. In a copy activity just create a REST dataset as a source, use base and relative urls and set a pagination rule. The alternative way is coding it in a notebook using Python.

I think parquet files are compressed by default (gzip) and therefore there is no need to compress them anymore.