1|Page
GCP Professional Data Engineer Certification
Exam Newest 2025/2026 With Complete
Questions And Correct Answers |Already Graded
A+||Brand New Version!|
A developer is planning a mobile application for your company's
customers to use to track information about their accounts. The
developer is asking for your advice on storage technologies. In one case,
the developer explains that they want to write messages each time a
significant event occurs, such as the client opening, viewing, or deleting
an account. This data is collected for compliance reasons, and the
developer wants to minimize administrative overhead. What system
would you recommend for storing this data?
A. Cloud SQL using MySQL
B. Cloud SQL using PostgreSQL
C. Cloud Datastore
D. Stackdriver Logging
D. The correct answer is D. Stackdriver Logging is the best option
because it is a managed service designed for storing logging data.
Neither Option A nor B is as good a fit because the developer would
have to design and maintain a relational data model and user interface to
view and manage log data. Option C, Cloud Datastore, would not
,2|Page
require a fixed data model, but it would still require the developer to
create and maintain a user interface to manage log events.
You are responsible for developing an ingestion mechanism for a large
number of IoT sensors. The ingestion service should accept data up to 10
minutes late. The service should also perform some transformations
before writing the data to a database. Which of the managed services
would be the best option for managing late arriving data and performing
transformations?
A. Cloud Dataproc
B. Cloud Dataflow
C. Cloud Dataprep
D. Cloud SQL
B. The correct answer is B. Cloud Dataflow is a stream and batch
processing service that is used for transforming data and processing
streaming data. Option A, Cloud Dataproc, is a managed Hadoop and
Spark service and not as well suited as Cloud Dataflow for the kind of
stream processing specified. Option C, Cloud Dataprep, is an interactive
tool for exploring and preparing data sets for analysis. Option D, Cloud
SQL, is a relational database service, so it may be used to store data, but
it is not a service specifically for ingesting and transforming data before
writing to a database.
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A team of analysts has collected several CSV datasets with a total size of
50 GB. They plan to store the datasets in GCP and use Compute Engine
instances to run RStudio, an interactive stats application. Data will be
loaded into RStudio using an RStudio data loading tool. Which of the
following is the most appropriate GCP storage service for the datasets?
A. Cloud Storage
B. Cloud Datastore
C. MongoDB
D. Bigtable
A. The correct answer is A, Cloud Storage, because the data in the files
is treated as an atomic unit of data that is loaded into RStudio. Options B
and C are incorrect because those are document databases and there is
no requirement for storing the data in semistructured format with
support for fully indexed querying. Also, MongoDB is not a GCP
service. Option D is incorrect because, although you could load CSV
data into a Bigtable table, the volume of data is not sufficient to warrant
using Bigtable.
A team of analysts has collected several terabytes of telemetry data in
CSV datasets. They plan to store the datasets in GCP and query and
analyze the data using SQL. Which of the following is the most
appropriate GCP storage service for the datasets?
A. Cloud SQL
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B. Cloud Spanner
C. BigQuery
D. Bigtable
C. The correct answer is C, BigQuery, which is a managed analytical
database service that supports SQL and scales to petabyte volumes of
data. Options A and B are incorrect because both are used for transaction
processing applications, not analytics. Option D is incorrect because
Bigtable does not support SQL.
You have been hired to consult with a startup that is developing software
for self-driving vehicles. The company's product uses machine learning
to predict the trajectory of persons and vehicles. Currently, the software
is being developed using 20 vehicles, all located in the same city. IoT
data is sent from vehicles every 60 seconds to a MySQL database
running on a Compute Engine instance using an n2-standard-8 machine
type with 8 vCPUs and 16 GB of memory. The startup wants to review
their architecture and make any necessary changes to support tens of
thousands of self-driving vehicles, all transmitting IoT data every
second. The vehicles will be located across North America and Europe.
Approximately 4 KB of data is sent in each transmission. What changes
to the architecture would you recommend?
A. None. The current architecture is well suited to the use case.
B. Replace Cloud SQL with Cloud Spanner.
C. Replace Cl
GCP Professional Data Engineer Certification
Exam Newest 2025/2026 With Complete
Questions And Correct Answers |Already Graded
A+||Brand New Version!|
A developer is planning a mobile application for your company's
customers to use to track information about their accounts. The
developer is asking for your advice on storage technologies. In one case,
the developer explains that they want to write messages each time a
significant event occurs, such as the client opening, viewing, or deleting
an account. This data is collected for compliance reasons, and the
developer wants to minimize administrative overhead. What system
would you recommend for storing this data?
A. Cloud SQL using MySQL
B. Cloud SQL using PostgreSQL
C. Cloud Datastore
D. Stackdriver Logging
D. The correct answer is D. Stackdriver Logging is the best option
because it is a managed service designed for storing logging data.
Neither Option A nor B is as good a fit because the developer would
have to design and maintain a relational data model and user interface to
view and manage log data. Option C, Cloud Datastore, would not
,2|Page
require a fixed data model, but it would still require the developer to
create and maintain a user interface to manage log events.
You are responsible for developing an ingestion mechanism for a large
number of IoT sensors. The ingestion service should accept data up to 10
minutes late. The service should also perform some transformations
before writing the data to a database. Which of the managed services
would be the best option for managing late arriving data and performing
transformations?
A. Cloud Dataproc
B. Cloud Dataflow
C. Cloud Dataprep
D. Cloud SQL
B. The correct answer is B. Cloud Dataflow is a stream and batch
processing service that is used for transforming data and processing
streaming data. Option A, Cloud Dataproc, is a managed Hadoop and
Spark service and not as well suited as Cloud Dataflow for the kind of
stream processing specified. Option C, Cloud Dataprep, is an interactive
tool for exploring and preparing data sets for analysis. Option D, Cloud
SQL, is a relational database service, so it may be used to store data, but
it is not a service specifically for ingesting and transforming data before
writing to a database.
,3|Page
A team of analysts has collected several CSV datasets with a total size of
50 GB. They plan to store the datasets in GCP and use Compute Engine
instances to run RStudio, an interactive stats application. Data will be
loaded into RStudio using an RStudio data loading tool. Which of the
following is the most appropriate GCP storage service for the datasets?
A. Cloud Storage
B. Cloud Datastore
C. MongoDB
D. Bigtable
A. The correct answer is A, Cloud Storage, because the data in the files
is treated as an atomic unit of data that is loaded into RStudio. Options B
and C are incorrect because those are document databases and there is
no requirement for storing the data in semistructured format with
support for fully indexed querying. Also, MongoDB is not a GCP
service. Option D is incorrect because, although you could load CSV
data into a Bigtable table, the volume of data is not sufficient to warrant
using Bigtable.
A team of analysts has collected several terabytes of telemetry data in
CSV datasets. They plan to store the datasets in GCP and query and
analyze the data using SQL. Which of the following is the most
appropriate GCP storage service for the datasets?
A. Cloud SQL
, 4|Page
B. Cloud Spanner
C. BigQuery
D. Bigtable
C. The correct answer is C, BigQuery, which is a managed analytical
database service that supports SQL and scales to petabyte volumes of
data. Options A and B are incorrect because both are used for transaction
processing applications, not analytics. Option D is incorrect because
Bigtable does not support SQL.
You have been hired to consult with a startup that is developing software
for self-driving vehicles. The company's product uses machine learning
to predict the trajectory of persons and vehicles. Currently, the software
is being developed using 20 vehicles, all located in the same city. IoT
data is sent from vehicles every 60 seconds to a MySQL database
running on a Compute Engine instance using an n2-standard-8 machine
type with 8 vCPUs and 16 GB of memory. The startup wants to review
their architecture and make any necessary changes to support tens of
thousands of self-driving vehicles, all transmitting IoT data every
second. The vehicles will be located across North America and Europe.
Approximately 4 KB of data is sent in each transmission. What changes
to the architecture would you recommend?
A. None. The current architecture is well suited to the use case.
B. Replace Cloud SQL with Cloud Spanner.
C. Replace Cl
