Question 1

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

Options :

A : Windows at every 100 MB of data

B : Single, Global Window

C : Windows at every 1 minute

D : Windows at every 10 minutes

Answer: B

Question 2

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?

Options :

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.

Answer: B

Question 3

You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?

Options :

A : Make a call to the Stackdriver API to list all logs, and apply an advanced filter.

B : In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.

C : In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.

D : Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.

Answer: B

Question 4

A team of researchers is running a high performance distributed computing platform on premises but wants to migrate to Google Cloud. The platform uses virtual machines. The researchers want to be able to scale up the number of virtual machines in the cluster based on CPU load. What would you recommend they use?

Options :

A : Kubernetes cluster

B : Managed instance groups

C : Unmanaged instance groups

D : Cloud Run

Answer: B

Question 5

You work for a bank. You have a labelled dataset that contains information on already granted loan application and whether these applications have been defaulted. You have been asked to train a model to predict default rates for credit applicants. What should you do?

Options :

A : Increase the size of the dataset by collecting additional data.

B : Train a linear regression to predict a credit default risk score.

C : Remove the bias from the data and collect applications that have been declined loans.

D : Match loan applicants with their social profiles to enable feature engineering.

Answer: B

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