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Google Data Engineer Sample Questions:

1. As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.

A) Create distinct groups for various teams, and specify groups in Cloud IAM policies.
B) Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
C) Use Cloud Deployment Manager to automate access provision.
D) Introduce resource hierarchy to leverage access control policy inheritance.
E) Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
F) For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces

2. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .

A) master node
B) conditional node
C) application node
D) worker node

3. Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

A) A processing time trigger
B) The with Allowed Lateness method
C) An hourly watermark
D) An event time trigger

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

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

5. 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.

Solutions: