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Google Data Engineer Sample Questions:
1. You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You've collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?
A) Use Cloud Vision AutoML with the existing dataset.
B) Use Cloud Vision AutoML, but reduce your dataset twice.
C) Use Cloud Vision API by providing custom labels as recognition hints.
D) Train your own image recognition model leveraging transfer learning techniques.
2. If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?
A) Use at least 300 GB of data.
B) Run your test for at least 10 minutes.
C) Before you test, run a heavy pre-test for several minutes.
D) Do not use a production instance.
3. All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.
A) after
B) once
C) only if
D) before
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) 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.
B) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
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) Add a new column called FullName to the Users tabl
E) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
F) Use BigQuery to export the data for the table to a CSV fil
5. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?
A) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
B) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
C) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
D) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: E | Question # 5 Answer: A |


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