Learn with Google : GCP-DE training material for 100% pass

Google GCP-DE Exam Overview:

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

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

3. Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective?

A) Use K-means Clustering to detect faces in the pixels.
B) Use feature engineering to add features for eyes, noses, and mouths to the input data.
C) Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.
D) Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.

4. What are the minimum permissions needed for a service account used with Google Dataproc?

A) Execute to Google Cloud Storage; write to Google Cloud Logging
B) Read and write to Google Cloud Storage; write to Google Cloud Logging
C) Execute to Google Cloud Storage; execute to Google Cloud Logging
D) Write to Google Cloud Storage; read to Google Cloud Logging

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

Solutions: