DATA ENGINEERING PROFESSIONAL EXAM
REVIEW SET 2026 BUNDLED CONTENT FULLY
SOLVED
◉ 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. Answer: 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.
,◉ 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. Answer: 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
B. Cloud Spanner
,C. BigQuery
D. Bigtable. Answer: 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. Answer: C. The correct answer is C. Bigtable is the best
storage service for IoT data, especially when a large number of
devices will be sending data at short intervals. Option A is incorrect,
because Cloud SQL is designed for transaction processing at a
, regional level. Option B is incorrect because Cloud Spanner is
designed for transaction processing, and although it scales to global
levels, it is not the best option for IoT data. Option D is incorrect
because there is no need for indexed, semi-structured data.
◉ As a member of a team of game developers, you have been tasked
with devising a way to track players' possessions. Possessions may
be purchased from a catalog, traded with other players, or awarded
for game activities. Possessions are categorized as clothing, tools,
books, and coins. Players may have any number of possessions of
any type. Players can search for other players who have particular
possession types to facilitate trading. The game designer has
informed you that there will likely be new types of possessions and
ways to acquire them in the future. What kind of a data store would
you recommend using?
A. Transactional database
B. Wide-column database
C. Document database
D. Analytic database. Answer: C. The correct answer is C because the
requirements call for a semi-structured schema. You will need to
search players' possessions and not just look them up using a single
key because of the requirement for facilitating trading. Option A is
not correct. Transactional databases have fixed schemas, and this
use case calls for a semi-structured schema. Option B is incorrect
because it does not support indexed lookup, which is needed for
REVIEW SET 2026 BUNDLED CONTENT FULLY
SOLVED
◉ 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. Answer: 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.
,◉ 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. Answer: 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
B. Cloud Spanner
,C. BigQuery
D. Bigtable. Answer: 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. Answer: C. The correct answer is C. Bigtable is the best
storage service for IoT data, especially when a large number of
devices will be sending data at short intervals. Option A is incorrect,
because Cloud SQL is designed for transaction processing at a
, regional level. Option B is incorrect because Cloud Spanner is
designed for transaction processing, and although it scales to global
levels, it is not the best option for IoT data. Option D is incorrect
because there is no need for indexed, semi-structured data.
◉ As a member of a team of game developers, you have been tasked
with devising a way to track players' possessions. Possessions may
be purchased from a catalog, traded with other players, or awarded
for game activities. Possessions are categorized as clothing, tools,
books, and coins. Players may have any number of possessions of
any type. Players can search for other players who have particular
possession types to facilitate trading. The game designer has
informed you that there will likely be new types of possessions and
ways to acquire them in the future. What kind of a data store would
you recommend using?
A. Transactional database
B. Wide-column database
C. Document database
D. Analytic database. Answer: C. The correct answer is C because the
requirements call for a semi-structured schema. You will need to
search players' possessions and not just look them up using a single
key because of the requirement for facilitating trading. Option A is
not correct. Transactional databases have fixed schemas, and this
use case calls for a semi-structured schema. Option B is incorrect
because it does not support indexed lookup, which is needed for
