Databricks Certified Data Engineer - Associate
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In a Databricks workspace, you are tasked with implementing a scalable and efficient process to periodically archive old notebooks and related data to optimize storage usage and maintain workspace organization. The solution must minimize manual intervention, adhere to compliance requirements, and be cost-effective. Considering these constraints, which of the following strategies would be the BEST to achieve this goal? (Choose one option)
A
Manually review each notebook and dataset periodically to identify and archive those that are no longer in use, ensuring direct control over what is archived.
B
Utilize the Databricks API to develop an automated workflow that identifies and archives notebooks and data based on customizable criteria such as last accessed date or size, ensuring consistency and reducing manual effort.
C
Rely on Databricks' built-in data retention policies to automatically manage the archiving and deletion of old notebooks and data, leveraging out-of-the-box functionality without additional development.
D
Develop a custom script that periodically scans the workspace for old notebooks and data, then moves them to a separate storage location, offering flexibility but requiring ongoing maintenance.