Explanation:
The most efficient approach involves using Data Catalog's native integrations for automatic cataloging of BigQuery and Pub/Sub resources, which significantly reduces manual effort. For PostgreSQL tables, utilizing the Data Catalog API offers a straightforward method to add metadata, enhancing discoverability. This strategy minimizes development and configuration work while maximizing data discoverability across the organization's platforms.
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Your organization's data assets are distributed across BigQuery, Pub/Sub, and a PostgreSQL instance on Compute Engine. With various domains and teams accessing the data, locating existing data assets has become a challenge. What is the most efficient method to improve data discoverability across these platforms with minimal development and configuration efforts?
A
Leverage Data Catalog for automatic cataloging of BigQuery datasets and Pub/Sub topics, and use Data Catalog APIs for manual cataloging of PostgreSQL tables.
B
Utilize Data Catalog to automatically catalog BigQuery datasets, and employ Data Catalog APIs for manual cataloging of Pub/Sub topics and PostgreSQL tables.
C
Apply Data Catalog for automatic cataloging of BigQuery datasets and Pub/Sub topics, and develop custom connectors for manual cataloging of PostgreSQL tables.
D
Develop custom connectors for manual cataloging of BigQuery datasets, Pub/Sub topics, and PostgreSQL tables.
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