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

2. You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

A) Sink API
B) PCollection
C) Pipeline
D) Transform

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

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

4. You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

A) Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
B) Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
C) Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
D) Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
E) Create an authorized view in BigQuery to restrict access to tables with sensitive data.

5. You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

A) Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
B) Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
C) Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
D) Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.

Solutions: