Google Professional Data Engineer Question 46
Select 2Google Cloud PlatformYou are working as a data engineer for a retail company that stores vast amounts of structured and unstructured data in Google Cloud. The company wants to improve data governance by enabling efficient data discovery and ensuring data compliance across different teams. Which combination of Google Cloud tools will best support this use case?
- A
Use Data Catalog to create metadata tags and enable data discovery.
- B
Use BigQuery to store and analyze metadata for governance purposes.
- C
Use Cloud DLP (Data Loss Prevention) to classify and protect sensitive data.
- D
Use Cloud Storage Lifecycle Management to automatically delete old data.
- E
Use Pub/Sub to create real-time notifications for data schema changes.
Show answer and explanation
Correct answers: A, C
Explanation
Efficient data governance involves managing metadata for discovery and compliance. Data Catalog is the ideal tool for metadata tagging and discovery, while Cloud DLP ensures sensitive data is identified and handled properly. These tools work together to enhance data governance in Google Cloud.
- A. Correct.
Data Catalog is specifically designed for metadata management, tagging, and enabling efficient data discovery. It is a key tool for data governance.
- B. Incorrect.
While BigQuery is excellent for analyzing large datasets, it is not a specialized tool for metadata management or data discovery, which is the focus of the question.
- C. Correct.
Cloud DLP helps classify, label, and protect sensitive data, making it an essential tool for data compliance and governance.
- D. Incorrect.
Cloud Storage Lifecycle Management is useful for managing data lifecycle, such as deleting or archiving data, but it does not address metadata management or data discovery.
- E. Incorrect.
Pub/Sub is a messaging service for real-time communication between systems, but it is not directly related to metadata management or data discovery.