Microsoft Azure Data Engineer Associate - DP-203
Get started today
Ultimate access to all questions.
Comments
Loading comments...
Ultimate access to all questions.
You are tasked with integrating a Jupyter notebook into a data pipeline for a financial services company. The notebook must process daily transaction data, perform anomaly detection, and update a Delta Lake. Describe the steps you would take to ensure the notebook is seamlessly integrated into the pipeline, including how you would handle potential errors and data retention policies.
A
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.
B
Manually execute the notebook daily, use Python try-except blocks for error handling, and configure the Delta Lake for indefinite data retention.
C
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.
D
Schedule the notebook using cron jobs, handle exceptions by restarting the notebook, and set a rolling data retention policy in the Delta Lake.