Databricks Certified Data Engineer - Associate
Comments
Loading comments...
Ultimate access to all questions.
In the context of data governance within an Azure Databricks environment, a company is looking to implement a strategy that ensures the accuracy and completeness of their data to support decision-making processes. The company operates in a highly regulated industry where data integrity is paramount. Considering the need for cost-effectiveness, scalability, and compliance with industry standards, which of the following data governance areas should be prioritized, and why? Choose the BEST option from the following:
A
Data Quality: Implementing automated data validation and cleansing processes to ensure the accuracy and completeness of data, which is crucial for reliable analytics and reporting.
B
Data Security: Deploying advanced encryption and access control mechanisms to protect data from unauthorized access, ensuring data confidentiality and integrity.
C
Data Compliance: Establishing data retention and privacy policies to adhere to regulatory requirements, minimizing legal risks and ensuring data is handled according to industry standards.
D
Data Lifecycle Management: Automating data archiving and purging processes to manage data from creation to retirement, optimizing storage costs and ensuring data relevance.