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Google Data Engineer Sample Questions:

1. Which of these sources can you not load data into BigQuery from?

A) Google Drive
B) Google Cloud Storage
C) File upload
D) Google Cloud SQL

2. When a Cloud Bigtable node fails, is lost.

A) no data
B) the last transaction
C) all data
D) the time dimension

3. What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

A) OutputCriteria
B) Windows
C) Sessions
D) Triggers

4. You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
B) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
C) Use BigQuery to export the data for the table to a CSV fil
D) Add a new column called FullName to the Users tabl
E) 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.
F) 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 FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.

5. Each analytics team in your organization is running BigQuery jobs in their own projects. You want to enable each team to monitor slot usage within their projects. What should you do?

A) Create a Stackdriver Monitoring dashboard based on the BigQuery metric query/scanned_bytes
B) Create a log export for each project, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric
C) Create a Stackdriver Monitoring dashboard based on the BigQuery metric slots/allocated_for_project
D) Create an aggregated log export at the organization level, capture the BigQuery job execution logs, create a custom metric based on the totalSlotMs, and create a Stackdriver Monitoring dashboard based on the custom metric

Solutions: