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Answer: Utilize the search functionality in the Data Catalog to look for 'employee_nu'.
Option A is correct because the Data Catalog provides a centralized, searchable metadata service for discovering and understanding data assets across Google Cloud Platform, including BigQuery. Searching for 'employee_nu' in the Data Catalog is the most straightforward and efficient method. Options B, C, and D involve more complex and resource-intensive processes, such as scripting or deploying Dataflow jobs, which are unnecessary for this simple search task. The Data Catalog's native indexing and search capabilities make it the optimal choice for quickly identifying datasets with specific columns.
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Your logistics company has accumulated extensive data over the years, utilizing BigQuery for data warehousing. Multiple teams frequently analyze thousands of datasets across hundreds of projects. The CIO has tasked you with identifying all datasets containing an 'employee_nu' column with minimal effort. What is the most efficient method to accomplish this?
A
Utilize the search functionality in the Data Catalog to look for 'employee_nu'.
B
Develop a shell script to iterate through all organization projects, using the bq command line tool to search for tables with the 'employee_nu' column.
C
Create a shell script to loop through all projects, executing a query on the INFORMATION_SCHEMA.COLUMNS view to locate the 'employee_nu' column.
D
Implement a Dataflow job to scan all projects, querying the INFORMATION_SCHEMA.COLUMNS view for the 'employee_nu' column.