Google Professional Data Engineer
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As a data engineer for a large fast food restaurant chain with over 400,000 employees, you are responsible for managing employee information stored in Google BigQuery. The employee data is currently held in a Users table, which has separate fields for FirstName and LastName. An IT team member is developing an application and has requested that you adjust the schema and data so the application can query a FullName field. This FullName field should contain the concatenated values of the FirstName and LastName fields, separated by a space, for each employee. How can you modify the schema and data to make the FullName field available while minimizing costs?
A
Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
B
Add a new column called FullName to the Users table. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
C
Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
D
Use BigQuery to export the data for the table to a CSV file. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullName. Run a BigQuery load job to load the new CSV file into BigQuery.