Question 1

You have a BigQuery dataset named "customers". All tables will be tagged by using a Data Catalog tagtemplate named "gdpr". The template contains one mandatory field, "has sensitive data~. with a boolean value.All employees must be able to do a simple search and find tables in the dataset that have either true or false inthe "has sensitive data" field. However, only the Human Resources (HR) group should be able to see the datainside the tables for which "hass-ensitive-data" is true. You give the all employees group thebigquery.metadataViewer and bigquery.connectionUser roles on the dataset. You want to minimizeconfiguration overhead. What should you do next?

Options :

A : Create the "gdpr" tag template with private visibility. Assign the bigquery -dataViewer role to the HRgroup on the tables that contain sensitive data.

B : Create the ~gdpr" tag template with private visibility. Assign the datacatalog. tagTemplateViewer roleon this tag to the all employeesgroup, and assign the bigquery.dataViewer role to the HR group on the tables that contain sensitive data.

C : Create the "gdpr" tag template with public visibility. Assign the bigquery. dataViewer role to the HRgroup on the tables that containsensitive data.

D : Create the "gdpr" tag template with public visibility. Assign the datacatalog. tagTemplateViewer role onthis tag to the all employees.group, and assign the bijquery.dataViewer role to the HR group on the tables that contain sensitive data.

Answer: D

Question 2

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

Question 3

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 4

Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low. You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

Options :

A : Introduce data compression for each file to increase the rate file of file transfer.

B : Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.

C : Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.

D : Assemble 1,000 files into a tape archive (TAR) file. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.

E : Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.

Answer: A

Question 5

Which role must be assigned to a service account used by the virtual machines in a Dataproc cluster so they can execute jobs?

Options :

A : Dataproc Worker

B : Dataproc Viewer

C : Dataproc Runner

D : Dataproc Editor

Answer: A

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