Google Professional Data Engineer Exam Questions Instant Access

Question 1

You are testing a Dataflow pipeline to ingest and transform text files. The files are compressed gzip, errors are written to a dead-letter queue, and you are using Sidelnputs to join data You noticed that the pipeline is taking longer to complete than expected, what should you do to expedite the Dataflow job?

ASwitch to compressed Avro files

BReduce the batch size

CRetry records that throw an error

DUse CoGroupByKey instead of the Sidelnput

Answer : B

Question 2

You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You've collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?

AUse Cloud Vision AutoML with the existing dataset.

BUse Cloud Vision AutoML, but reduce your dataset twice.

CUse Cloud Vision API by providing custom labels as recognition hints.

DTrain your own image recognition model leveraging transfer learning techniques.

Answer : A

Question 3

You need (o give new website users a globally unique identifier (GUID) using a service that takes in data points and returns a GUID This data is sourced from both internal and external systems via HTTP calls that you will make via microservices within your pipeline There will be tens of thousands of messages per second and that can be multithreaded, and you worry about the backpressure on the system How should you design your pipeline to minimize that backpressure?

ACall out to the service via HTTP

BCreate the pipeline statically in the class definition

CCreate a new object in the startBundle method of DoFn

DBatch the job into ten-second increments

Answer : A

Question 4

If a dataset contains rows with individual people and columns for year of birth, country, and income, how many of the columns are continuous and how many are categorical?

A1 continuous and 2 categorical

B3 categorical

C3 continuous

D2 continuous and 1 categorical

Answer : D

The columns can be grouped into two types---categorical and continuous columns:

A column is called categorical if its value can only be one of the categories in a finite set. For example, the native country of a person (U.S., India, Japan, etc.) or the education level (high school, college, etc.) are categorical columns.

A column is called continuous if its value can be any numerical value in a continuous range. For example, the capital gain of a person (e.g. $14,084) is a continuous column.

Year of birth and income are continuous columns. Country is a categorical column.

You could use bucketization to turn year of birth and/or income into categorical features, but the raw columns are continuous.

Question 5

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?

ACreate an API using App Engine to receive and send messages to the applications

BUse a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

CCreate a table on Cloud SQL, and insert and delete rows with the job information

DCreate a table on Cloud Spanner, and insert and delete rows with the job information

Answer : A

Question 6

You are working on a sensitive project involving private user data. You have set up a project on Google Cloud Platform to house your work internally. An external consultant is going to assist with coding a complex transformation in a Google Cloud Dataflow pipeline for your project. How should you maintain users' privacy?

AGrant the consultant the Viewer role on the project.

BGrant the consultant the Cloud Dataflow Developer role on the project.

CCreate a service account and allow the consultant to log on with it.

DCreate an anonymized sample of the data for the consultant to work with in a different project.

Answer : C

Question 7

You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

Acron

BCloud Composer

CCloud Scheduler

DWorkflow Templates on Cloud Dataproc

Answer : B

Google Cloud Certified Professional Data Engineer Exam Questions