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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

A) Cloud Datastore
B) Cloud BigTable
C) Cloud SQL
D) BigQuery

2. By default, which of the following windowing behavior does Dataflow apply to unbounded data sets?

A) Windows at every 1 minute
B) Windows at every 10 minutes
C) Windows at every 100 MB of data
D) Single, Global Window

3. You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

A) Build and train a text classification model using TensorFlo
B) Process the generated Sentiment Analysis as labels.
C) Call the model from your application and process the results as labels.
D) Process the generated Entity Analysis as labels.
E) Deploy the model using a KubernetesEngine cluste
F) Build and train a text classification model using TensorFlo
G) Call the model from your application and process the results as labels.
H) Call the Cloud Natural Language API from your applicatio
I) Call the Cloud Natural Language API from your applicatio
J) Deploy the model using Cloud Machine Learning Engin

4. You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A) Create a temporary table in Cloud Bigtable that will act as a buffer for new data
B) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
C) Increase the number of max workers
D) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
E) Use a larger instance type for your Cloud Dataflow workers
F) Create a temporary table in Cloud Spanner that will act as a buffer for new data
G) Change the zone of your Cloud Dataflow pipeline to run in us-central1

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

Solutions: