Free Access Google.Professional-Data-Engineer.v2022-02-11.q268 Practice Test (Page 22)

Question 101

When you design a Google Cloud Bigtable schema it is recommended that you
_________.

A.Avoid schema designs that are based on NoSQL concepts

B.Create schema designs that are based on a relational database design

C.Avoid schema designs that require atomicity across rows

D.Create schema designs that require atomicity across rows

Question 102

You are implementing security best practices on your data pipeline. Currently, you are manually executing
jobs as the Project Owner. You want to automate these jobs by taking nightly batch files containing non-
public information from Google Cloud Storage, processing them with a Spark Scala job on a Google Cloud
Dataproc cluster, and depositing the results into Google BigQuery.
How should you securely run this workload?

A.Use a service account with the ability to read the batch files and to write to BigQuery

B.Restrict the Google Cloud Storage bucket so only you can see the files

C.Grant the Project Owner role to a service account, and run the job with it

D.Use a user account with the Project Viewer role on the Cloud Dataproc cluster to read the batch files
and write to BigQuery

Question 103

Cloud Dataproc charges you only for what you really use with _____ billing.

A.month-by-month

B.minute-by-minute

C.week-by-week

D.hour-by-hour

Question 104

Government regulations in your industry mandate that you have to maintain an auditable record of access
to certain types of data. Assuming that all expiring logs will be archived correctly, where should you store
data that is subject to that mandate?

A.In a bucket on Cloud Storage that is accessible only by an AppEngine service that collects user
information and logs the access before providing a link to the bucket.

B.Encrypted on Cloud Storage with user-supplied encryption keys. A separate decryption key will be
given to each authorized user.

C.In Cloud SQL, with separate database user names to each user. The Cloud SQL Admin activity logs
will be used to provide the auditability.

D.In a BigQuery dataset that is viewable only by authorized personnel, with the Data Access log used to
provide the auditability.

Question 105

You are creating a new pipeline in Google Cloud to stream IoT data from Cloud Pub/Sub through Cloud Dataflow to BigQuery. While previewing the data, you notice that roughly 2% of the data appears to be corrupt.
You need to modify the Cloud Dataflow pipeline to filter out this corrupt data. What should you do?

A.Add a SideInput that returns a Boolean if the element is corrupt.

B.Add a ParDo transform in Cloud Dataflow to discard corrupt elements.

C.Add a Partition transform in Cloud Dataflow to separate valid data from corrupt data.

D.Add a GroupByKey transform in Cloud Dataflow to group all of the valid data together and discard the rest.

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Question 101

Question 102

Question 103

Question 104

Question 105

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