Google Cloud Professional Machine Learning Engineer — Question 31

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?

Answer options

• 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.

Correct answer: A

Explanation

The correct answer is A because Data Catalog allows for efficient searching of datasets using keywords found in table descriptions, making it easier to locate the right table. Option B does not assist in finding the table itself but rather involves tagging resources after the fact. Option C, while useful for mapping, requires additional maintenance and querying, which is less efficient. Option D provides a list of tables but does not offer a straightforward way to find tables based on their descriptions.