Google Professional Data Engineer Pde Practice Test - Set 1

Test your knowledge with this Google Professional Data Engineer Pde mock exam. Get real-world IT questions and prepare for certification success.

Google Professional Data Engineer (PDE) - Exam Information

Exam Information

Exam Code

Google Professional Data Engineer Pde

Exam Title

Google Professional Data Engineer (PDE)

Vendor

Google

Difficulty

Advanced

Duration

120 Minutes

Question Format

Multiple Choice

Last Updated

March 12, 2025

Tests ability to design and implement data processing systems in Google Cloud.

Practice Test

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1. Which Google Cloud service is used for large-scale data warehousing and analytics?

BigQuery

Cloud Spanner

Cloud SQL

Dataflow

2. Which Google Cloud service is used for real-time data streaming and processing?

Dataflow

BigQuery

Cloud Pub/Sub

Cloud Storage

3. Which Google Cloud service is used for managing NoSQL databases?

Firestore

Cloud SQL

Bigtable

Spanner

4. Which Google Cloud service is used for batch and stream data processing?

Dataflow

BigQuery

Cloud Storage

Pub/Sub

5. Which Google Cloud service is used for real-time messaging and event ingestion?

Pub/Sub

Dataflow

BigQuery

Cloud Storage

6. Which Google Cloud service is used for managing relational databases?

Cloud SQL

Bigtable

Firestore

Spanner

7. Which Google Cloud service is used for globally distributed relational databases?

Cloud Spanner

Cloud SQL

Bigtable

Firestore

8. Which Google Cloud service is used for managing time-series data?

Bigtable

Cloud SQL

Firestore

Spanner

9. Which Google Cloud service is used for data integration and ETL processes?

Dataflow

BigQuery

Cloud Storage

Pub/Sub

10. Which Google Cloud service is used for storing and analyzing large datasets?

BigQuery

Cloud Storage

Cloud SQL

Firestore

11. Which Google Cloud service is used for managing in-memory caching?

Memorystore

Cloud Storage

Cloud SQL

Firestore

12. Which Google Cloud service is used for managing data pipelines?

Dataflow

BigQuery

Cloud Storage

Pub/Sub

13. Which Google Cloud service is used for managing data lakes?

Cloud Storage

BigQuery

Cloud SQL

Firestore

14. Which Google Cloud service is used for managing data warehouses?

BigQuery

Cloud Storage

Cloud SQL

Firestore

15. Which Google Cloud service is used for managing data migration?

Cloud Data Transfer

BigQuery

Cloud Storage

Pub/Sub

16. Which Google Cloud service is used for managing data governance?

Dataplex

BigQuery

Cloud Storage

Pub/Sub

17. Which Google Cloud service is used for managing data cataloging?

Data Catalog

BigQuery

Cloud Storage

Pub/Sub

18. Which Google Cloud service is used for managing data encryption?

Cloud KMS

BigQuery

Cloud Storage

Pub/Sub

19. Which Google Cloud service is used for managing data security?

Security Command Center

BigQuery

Cloud Storage

Pub/Sub

20. Which Google Cloud service is used for managing data backups?

Cloud Storage

BigQuery

Cloud SQL

Firestore

21. Which service is best for analyzing petabytes of data with SQL queries?

BigQuery

Cloud SQL

Cloud Spanner

Dataproc

22. What is the primary advantage of using Cloud Dataflow over running Apache Beam on Dataproc?

Fully managed serverless execution

Lower cost

Faster processing

Better Hadoop integration

23. Which service would you use to migrate on-premises Hadoop jobs to Google Cloud?

Dataproc

Dataflow

BigQuery

Cloud Composer

24. What is the purpose of BigQuery's partitioning feature?

To improve query performance on large tables

To encrypt data

To reduce storage costs

To enable cross-region replication

25. Which service provides a unified analytics data lake platform?

Dataplex

BigQuery

Cloud Storage

Data Catalog

26. What is the primary use case for Cloud Spanner?

Globally distributed relational database

Data warehousing

Stream processing

Machine learning

27. Which command would you use to load data from Cloud Storage into BigQuery?

bq load

gcloud data transfer

gsutil cp

bq extract

28. What is the purpose of Data Catalog?

Metadata management and discovery

Data processing

Data encryption

Data visualization

29. Which service is best for processing real-time streaming data?

Dataflow

Dataproc

BigQuery

Cloud Composer

30. What is the primary benefit of BigQuery ML?

Build ML models using SQL

Faster query performance

Lower storage costs

Real-time data ingestion

31. Which service provides a managed Apache Airflow environment?

Cloud Composer

Dataflow

Dataproc

BigQuery

32. What is the purpose of Cloud Pub/Sub?

Event ingestion and delivery

Data warehousing

Batch processing

Machine learning

33. Which database service is best for time-series data?

Bigtable

Cloud SQL

Firestore

Spanner

34. What is the primary advantage of using Dataflow templates?

Pre-built pipelines for common use cases

Lower cost

Faster execution

Better monitoring

35. Which service would you use to schedule BigQuery queries?

Cloud Scheduler

Dataflow

Cloud Composer

Dataproc

36. What is the purpose of BigQuery's clustering feature?

To colocate related data for faster queries

To encrypt data

To reduce storage costs

To enable replication

37. Which service provides a managed Spark and Hadoop environment?

Dataproc

Dataflow

BigQuery

Cloud Composer

38. What is the primary use case for Cloud Data Fusion?

GUI-based ETL/ELT pipelines

Real-time analytics

Data warehousing

Machine learning

39. Which command would you use to export data from BigQuery to Cloud Storage?

bq extract

gcloud data transfer

gsutil cp

bq load

40. What is the purpose of Dataprep?

Visual data preparation and cleaning

Data processing

Data encryption

Data visualization

41. Which service is best for ad-hoc analysis of large datasets?

BigQuery

Cloud SQL

Dataproc

Dataflow

42. What is the primary advantage of using Bigtable over BigQuery?

Low-latency reads/writes

SQL support

Cost efficiency

Global replication

43. Which service would you use to transform and clean data before loading to BigQuery?

Dataflow

Dataproc

Cloud Composer

Dataprep

44. What is the purpose of Cloud Data Loss Prevention (DLP)?

Identify and protect sensitive data

Process streaming data

Manage databases

Visualize data

45. Which service provides a unified view of data across multiple sources?

Dataplex

BigQuery

Data Catalog

Cloud Storage

46. What is the primary use case for Cloud Composer?

Workflow orchestration

Real-time analytics

Data warehousing

Machine learning

47. Which command would you use to create a BigQuery dataset?

bq mk

gcloud data transfer

gsutil mb

bq query

48. What is the purpose of BigQuery BI Engine?

Accelerate dashboard queries

Process streaming data

Manage databases

Visualize data

49. Which service is best for high-throughput, low-latency NoSQL workloads?

Bigtable

Firestore

Cloud SQL

Spanner

50. What is the primary advantage of using Dataflow over Dataproc?

No cluster management required

Lower cost

Better Hadoop compatibility

Faster processing

The Google Professional Data Engineer Pde certification is a globally recognized credential for IT professionals. This practice test helps you prepare by covering key topics like hardware, networking, troubleshooting, and security.

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Google Professional Data Engineer Pde Practice Test - Set 1

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