Google Professional Data Engineer Question 47
Single answerGoogle Cloud PlatformYour organization is building a centralized data lake on Google Cloud to store and manage large volumes of structured and unstructured data. To ensure data governance, you need to enable data discovery, cataloging, and lineage tracking for datasets stored in BigQuery and Cloud Storage. Which tool should you use to achieve this?
- A
Cloud Data Catalog
- B
BigQuery ML
- C
Cloud Pub/Sub
- D
Dataproc Metastore
Show answer and explanation
Correct answer: A
Explanation
Cloud Data Catalog is the appropriate choice for enabling data discovery, cataloging, and lineage tracking on Google Cloud. It integrates with BigQuery and Cloud Storage, providing a centralized metadata repository and tools to manage data governance effectively. The other options do not address the specific requirements for metadata management and discovery in this scenario.
- A. Correct.
Cloud Data Catalog is a fully managed metadata management service that enables data discovery, cataloging, and governance. It is specifically designed for use cases like yours to manage metadata for BigQuery, Cloud Storage, and other Google Cloud services.
- B. Incorrect.
BigQuery ML is used for building machine learning models directly in BigQuery and is not related to data governance, discovery, or cataloging.
- C. Incorrect.
Cloud Pub/Sub is a messaging service for event-driven systems, not a tool for cataloging or managing metadata.
- D. Incorrect.
Dataproc Metastore is a fully managed Apache Hive metastore service for metadata management in Dataproc, but it is not suitable for centralized data governance and discovery across BigQuery and Cloud Storage.