Use Azure Data Factory to schedule the notebook execution, implement basic exception handling within the notebook, and set a fixed data retention period in the Delta Lake.

Manually execute the notebook daily, use Python try-except blocks for error handling, and configure the Delta Lake for indefinite data retention.

Automate the notebook execution using Azure Databricks jobs, implement robust exception handling with logging, and configure the Delta Lake for dynamic data retention based on data volume.

Schedule the notebook using cron jobs, handle exceptions by restarting the notebook, and set a rolling data retention policy in the Delta Lake.