Updated: Aug 20, 2026
No. of Questions: 77 Questions & Answers with Testing Engine
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| Certification Vendor: | Google Cloud |
| Exam Name: | Google Cloud Professional Data Engineer Exam |
| Exam Number: | GCP-DE / PDE |
| Passing Score: | Not publicly disclosed (scaled scoring system) |
| Exam Format: | Multiple choice, Multiple select |
| Exam Price: | $200 USD (plus tax where applicable) |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | 2 years |
| Real Exam Qty: | 40 - 50 |
| Related Certifications: | Google Cloud Professional Cloud Architect Google Cloud Professional Data Analyst Google Cloud Associate Cloud Engineer |
| Available Languages: | English, Japanese |
| Recommended Training: | Official Exam Guide Google Cloud Professional Data Engineer Learning Path |
| Exam Registration: | Google Cloud Certification Registration |
| Sample Questions: | Google GCP-DE Sample Questions |
| Exam Way: | Online-proctored or onsite-proctored at authorized test centers |
| Pre Condition: | No mandatory prerequisites; recommended 3+ years industry experience, 1+ year working with Google Cloud data solutions |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Preparing data for analysis and machine learning | 13% | - Preparing data for ML
|
| Topic 2: Storing and managing data | 20% | - Optimizing storage performance and cost
|
| Topic 3: Ingesting and processing data | 25% | - Transforming data
|
| Topic 4: Maintaining and automating data workloads | 18% | - Operationalizing workloads
|
| Topic 5: Designing data processing systems | 24% | - Planning data solutions
|
1. You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?
A) Set the BigQuery dataset to be multi-regional
B) Set the BigQuery dataset to be multi-regional
C) In the event of an emergency, use the backup copy of the table.
D) Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
E) Set the BigQuery dataset to be regiona
F) Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
G) In the event of an emergency, use a point-in-time snapshot to recover the data.
H) Set the BigQuery dataset to be regiona
I) In the event of an emergency, use a point-in-time snapshot to recover the data.
J) In the event of an emergency, use the backup copy of the table.
2. If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?
A) Run your test for at least 10 minutes.
B) Use at least 300 GB of data.
C) Do not use a production instance.
D) Before you test, run a heavy pre-test for several minutes.
3. What are all of the BigQuery operations that Google charges for?
A) Queries and streaming inserts
B) Storage, queries, and loading data from a file
C) Storage, queries, and streaming inserts
D) Storage, queries, and exporting data
4. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?
A) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
B) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
C) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
D) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
5. You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?
A) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
B) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
C) Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
D) If that number falls below 4000, send an alert.
E) Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
F) Consume the stream of data in Cloud Dataflow using Kafka I
G) If that number falls below 4000, send an alert.
H) Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
I) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
J) Set a sliding time window of 1 hour every 5 minute
K) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
L) Consume the stream of data in Cloud Dataflow using Kafka I
M) Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
Solutions:
| Question # 1 Answer: I | Question # 2 Answer: C | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: H |
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