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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, but reduce your dataset twice.
B) Use Cloud Vision API by providing custom labels as recognition hints.
C) Train your own image recognition model leveraging transfer learning techniques.
D) Use Cloud Vision AutoML with the existing dataset.

2. All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.

A) only if
B) after
C) before
D) once

3. Cloud Dataproc is a managed Apache Hadoop and Apache service.

A) Ignite
B) Spark
C) Fire
D) Blaze

4. You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

A) Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
B) Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
C) Store the data in Google Cloud Datastor
D) Store the data in a file in a regional Google Cloud Storage bucke
E) Load the data every 30 minutes into a new partitioned table in BigQuery.
F) Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.

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

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

Solutions: