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?
To find the proper BigQuery table among thousands of datasets, the most efficient method is to use Data Catalog to search the datasets by using keywords in the table description. Data Catalog is a fully managed service that provides a highly scalable and agile metadata management system. It is specifically designed for this type of task, allowing you to quickly locate datasets based on their descriptions.
Should be A https://cloud.google.com/data-catalog/docs/concepts/overview
who is providing these answers?? Its clearly A. most of the answers are incorrect here.
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)
Went with A
Another vote for answer A from me.
I vote A
Another vote for A by me.
A should be correct
A is the only way
A without hesitation.
A) Data Catalog