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GCP PROFESSIONAL DATA ENGINEER CERTIFICATION EXAM LATEST 2025/2026
ACTUAL EXAM WITH COMPLETE QUESTIONS AND CORRECT DETAILED
ANSWERS (100% VERIFIED ANSWERS) |ALREADY GRADED A+| ||PROFESSOR
VERIFIED|| ||BRANDNEW!!!||
You are investigating long latencies in Cloud Bigtable query
response times. Most queries finish in less than 20 ms, but the
99th percentile queries can take up to 400 ms. You examine a
Key Visualizer heatmap and see two areas with bright colors
indicating hotspots. What could be causing those hotspots?
A. Improperly used secondary index
B. Less than optimal partition key
C. Improperly designed row-key
D. Failure to use a read replica - ANSWER-C. The correct
answer is C. Hotspots occur when a row-key design does not
adequately distribute read/write load for a given query
pattern. Option A is incorrect; Cloud Bigtable does not have
secondary indexes. Option B is incorrect; Cloud Bigtable
does not use partition keys. Options D is incorrect; the
hotspots are not caused by failure to use a read replica,
although using a read replica may reduce the load on the
nodes with hotspots.
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An IoT startup has hired you to review their Cloud Bigtable
design. The database stores data generated by over 100,000
sensors that send data every 60 seconds. Each row contains all
the data for one sensor sent during an hour. Hours always start at
the top of the hour. The row-key is the sensor ID concatenated to
the hour of the day followed by the date. What change, if any,
would you recommend to this design?
A. Use one row per sensor and 60-second datasets instead of
storing multiple datasets in a single row.
B. Start the row keyrow-key with the day and hour instead of the
sensor ID.
C. Allow hours to start an any arbitrary time to accommodate
differences in sensor clocks.
D. No change is recommended. - ANSWER-A. The correct
answer is A. This table should be designed as a tall and
narrow one with a single dataset in each row. Option B is
incorrect because starting a row-key with the date and hour
will lead to hotspotting. Option C is incorrect, since changing
the start time will not change the parts of the design that
make querying by ranges more difficult than they need to be.
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Option D is incorrect; the structure of rows should be
changed from wide to narrow.
Your company has a Cloud Bigtable database that requires strong
consistency, but it also requires high availability. You have
implemented Cloud Bigtable replication and specified single-
cluster routing in the app profile for the database. Some users
have noted that they occasionally receive query results
inconsistent with what they should have received. The problem
seems to correct itself within a minute. What could be the cause
of this problem?
A. Secondary indexes are being updated during the query and
return incorrect results when a secondary index is not fully
updated.
B. You have not specified an app configuration file that includes
single-cluster routing and use of replicas only for failover.
C. Tablets are being moved between nodes, which can cause
inconsistent query results.
D. The row-key is not properly designed. - ANSWER-B. The
correct answer is B. The only way to achieve strong
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consistency in Cloud Bigtable is by having all reads routed
from a single cluster and using the other replicas only for
failover. Option A is incorrect; Cloud Bigtable does not have
secondary indexes. Option C
is incorrect; moving tablets does not impact read
consistency. Option D is incorrect; a poor row-key design
can impact performance but not consistency.
You have been tasked with migrating a MongoDB database to
Cloud Spanner. MongoDB is a document database, similar to
Cloud Firestore. You would like to maintain some of the document
organization of the MongoDB design. What data type, available in
Cloud Spanner, would you use to define a column that can hold a
document-like structure?
A. Array
B. String
C. STRUCT
D. JSON - ANSWER-C. The correct answer is C; the STRUCT
data type is used to store ordered type fields, and this is the
closest to a document structure. Option A is incorrect; all
GCP PROFESSIONAL DATA ENGINEER CERTIFICATION EXAM LATEST 2025/2026
ACTUAL EXAM WITH COMPLETE QUESTIONS AND CORRECT DETAILED
ANSWERS (100% VERIFIED ANSWERS) |ALREADY GRADED A+| ||PROFESSOR
VERIFIED|| ||BRANDNEW!!!||
You are investigating long latencies in Cloud Bigtable query
response times. Most queries finish in less than 20 ms, but the
99th percentile queries can take up to 400 ms. You examine a
Key Visualizer heatmap and see two areas with bright colors
indicating hotspots. What could be causing those hotspots?
A. Improperly used secondary index
B. Less than optimal partition key
C. Improperly designed row-key
D. Failure to use a read replica - ANSWER-C. The correct
answer is C. Hotspots occur when a row-key design does not
adequately distribute read/write load for a given query
pattern. Option A is incorrect; Cloud Bigtable does not have
secondary indexes. Option B is incorrect; Cloud Bigtable
does not use partition keys. Options D is incorrect; the
hotspots are not caused by failure to use a read replica,
although using a read replica may reduce the load on the
nodes with hotspots.
,2|Page
An IoT startup has hired you to review their Cloud Bigtable
design. The database stores data generated by over 100,000
sensors that send data every 60 seconds. Each row contains all
the data for one sensor sent during an hour. Hours always start at
the top of the hour. The row-key is the sensor ID concatenated to
the hour of the day followed by the date. What change, if any,
would you recommend to this design?
A. Use one row per sensor and 60-second datasets instead of
storing multiple datasets in a single row.
B. Start the row keyrow-key with the day and hour instead of the
sensor ID.
C. Allow hours to start an any arbitrary time to accommodate
differences in sensor clocks.
D. No change is recommended. - ANSWER-A. The correct
answer is A. This table should be designed as a tall and
narrow one with a single dataset in each row. Option B is
incorrect because starting a row-key with the date and hour
will lead to hotspotting. Option C is incorrect, since changing
the start time will not change the parts of the design that
make querying by ranges more difficult than they need to be.
,3|Page
Option D is incorrect; the structure of rows should be
changed from wide to narrow.
Your company has a Cloud Bigtable database that requires strong
consistency, but it also requires high availability. You have
implemented Cloud Bigtable replication and specified single-
cluster routing in the app profile for the database. Some users
have noted that they occasionally receive query results
inconsistent with what they should have received. The problem
seems to correct itself within a minute. What could be the cause
of this problem?
A. Secondary indexes are being updated during the query and
return incorrect results when a secondary index is not fully
updated.
B. You have not specified an app configuration file that includes
single-cluster routing and use of replicas only for failover.
C. Tablets are being moved between nodes, which can cause
inconsistent query results.
D. The row-key is not properly designed. - ANSWER-B. The
correct answer is B. The only way to achieve strong
, 4|Page
consistency in Cloud Bigtable is by having all reads routed
from a single cluster and using the other replicas only for
failover. Option A is incorrect; Cloud Bigtable does not have
secondary indexes. Option C
is incorrect; moving tablets does not impact read
consistency. Option D is incorrect; a poor row-key design
can impact performance but not consistency.
You have been tasked with migrating a MongoDB database to
Cloud Spanner. MongoDB is a document database, similar to
Cloud Firestore. You would like to maintain some of the document
organization of the MongoDB design. What data type, available in
Cloud Spanner, would you use to define a column that can hold a
document-like structure?
A. Array
B. String
C. STRUCT
D. JSON - ANSWER-C. The correct answer is C; the STRUCT
data type is used to store ordered type fields, and this is the
closest to a document structure. Option A is incorrect; all
