GCP-DE by Google Actual Free Exam Questions And Answers

Question 1

You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A. Use BigQuery to export the data for the table to a CSV fil

B. Add a new column called FullName to the Users tabl

C. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.

D. Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.

E. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.

F. Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.

Discussion 0

Correct Answer: E Vote an answer

Question 2

You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A. Create a table on Cloud Spanner, and insert and delete rows with the job information

B. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

C. Create a table on Cloud SQL, and insert and delete rows with the job information

D. Create an API using App Engine to receive and send messages to the applications

Discussion 0

Correct Answer: B Vote an answer

Question 3

You architect a system to analyze seismic dat
a. Your extract, transform, and load (ETL) process runs as a series of MapReduce jobs on an Apache Hadoop cluster. The ETL process takes days to process a data set because some steps are computationally expensive. Then you discover that a sensor calibration step has been omitted. How should you change your ETL process to carry out sensor calibration systematically in the future?

A. Develop an algorithm through simulation to predict variance of data output from the last MapReduce job based on calibration factors, and apply the correction to all data.

B. Add sensor calibration data to the output of the ETL process, and document that all users need to apply sensor calibration themselves.

C. Introduce a new MapReduce job to apply sensor calibration to raw data, and ensure all other MapReduce jobs are chained after this.

D. Modify the transformMapReduce jobs to apply sensor calibration before they do anything else.

Discussion 0

Correct Answer: D Vote an answer

Question 4

You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

A. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.

B. Re-create the tables using DD

C. Partition the tables by a column containing a TIMESTAMP or DATE Type.

D. Write an Apache Beam pipeline that creates a BigQuery table per data

E. Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.

F. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.

Discussion 0

Correct Answer: F Vote an answer

Question 5

When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A. VPN

B. SOCKS

C. HTTPS

D. HTTP

Discussion 0

Correct Answer: B Vote an answer

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

Question 6

What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

A. Triggers

B. Sessions

C. OutputCriteria

D. Windows

Discussion 0

Correct Answer: A Vote an answer

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Question 7

Which of the following is NOT true about Dataflow pipelines?

A. Dataflow pipelines can be programmed in Java

B. Dataflow pipelines can consume data from other Google Cloud services

C. Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner

D. Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources

Discussion 0

Correct Answer: C Vote an answer

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

Question 8

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. Create an authorized view in BigQuery to restrict access to tables with sensitive data.

B. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.

C. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP

D. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.

E. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.

Discussion 0

Correct Answer: A Vote an answer

Google Data Engineer - GCP-DE Exam Practice Test

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