How should you find the data that you need?

You recently joined an enterprise-scale company that has thousands of datasets. You know that there are accurate descriptions for each table in BigQuery, and you are searching for the proper BigQuery table to use for a model you are building on AI Platform.

How should you find the data that you need?
A . Use Data Catalog to search the BigQuery datasets by using keywords in the table description.
B. Tag each of your model and version resources on AI Platform with the name of the BigQuery table that was used for training.
C. Maintain a lookup table in BigQuery that maps the table descriptions to the table ID.
Query the lookup table to find the correct table ID for the data that you need.
D. Execute a query in BigQuery to retrieve all the existing table names in your project using the
INFORMATION_SCHEMA metadata tables that are native to BigQuery. Use the result o find the table that you need.

Answer: A

Explanation:

A should be the way to go for large datasets –This is also good but it is legacy way of checking: – NFORMATION_SCHEMA contains these views for table metadata: TABLES and TABLE_OPTIONS for metadata about tables. COLUMNS and COLUMN_FIELD_PATHS for metadata about columns and fields. PARTITIONS for metadata about table partitions (Preview)