Google Professional Data Engineer (GCP) Practice Exam
Google Cloud Certified Professional Data Engineer
About Google Cloud Certified - Professional Data Engineer Exam
The Professional Data Engineer exam enables data-driven decision making by collecting, transforming, and visualizing data. The sole objective of a Google Cloud Certified - Professional Data Engineer is to design, build, maintain, and troubleshoot data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of the systems.
Exam Pattern for Google Cloud Certified - Professional Data Engineer
- Language: English, Japanese, Spanish, and Portuguese.
- Length: 2 hours
- Types of Questions: Multiple Choice and Multiple Select
* Note the exam has no prerequisites and must be taken in-person at one of our testing center locations.
Course Outline
The Certified Professional Data Engineer exam covers the latest and updated exam topics -
Domain 1 - Understand designing data processing systems (~22% of the exam)
1.1 Designing for security and compliance. Considerations include:
- Identity and Access Management (e.g., Cloud IAM and organization policies)
- Data security (encryption and key management)
- Privacy (e.g., personally identifiable information, and Cloud Data Loss Prevention API)
- Regional considerations (data sovereignty) for data access and storage
- Legal and regulatory compliance
1.2 Designing for reliability and fidelity. Considerations include:
- Preparing and cleaning data (e.g., Dataprep, Dataflow, and Cloud Data Fusion)
- Monitoring and orchestration of data pipelines
- Disaster recovery and fault tolerance
- Making decisions related to ACID (atomicity, consistency, isolation, and durability) compliance and availability
- Data validation
1.3 Designing for flexibility and portability. Considerations include:
- Mapping current and future business requirements to the architecture
- Designing for data and application portability (e.g., multi-cloud and data residency requirements)
- Data staging, cataloging, and discovery (data governance)
- Designing data migrations. Considerations include:
- Analyzing current stakeholder needs, users, processes, and technologies and creating a plan to get to desired state
- Planning migration to Google Cloud (e.g., BigQuery Data Transfer Service, Database Migration Service, Transfer Appliance, Google Cloud networking, Datastream)
- Designing the migration validation strategy
- Designing the project, dataset, and table architecture to ensure proper data governance
Domain 3: Understanding to ingest and process the data (~25%)
2.1 Planning the data pipelines. Considerations include:
- Defining data sources and sinks
- Defining data transformation logic
- Networking fundamentals
- Data encryption
2.2 Building the pipelines. Considerations include:
- Data cleansing
- Identifying the services (e.g., Dataflow, Apache Beam, Dataproc, Cloud Data Fusion, BigQuery, Pub/Sub, Apache Spark, Hadoop ecosystem, and Apache Kafka)
- Transformations - Batch, Streaming (e.g., windowing, late arriving data), Language, Ad hoc data ingestion (one-time or automated pipeline)
- Data acquisition and import
- Integrating with new data sources
2.3 Deploying and operationalizing the pipelines. Considerations include:
- Job automation and orchestration (e.g., Cloud Composer and Workflows)
- CI/CD (Continuous Integration and Continuous Deployment)
Domain 3: Understand Storing the data (~20% of the exam)
3.1 Selecting storage systems. Considerations include:
- Analyzing data access patterns
- Choosing managed services (e.g., Bigtable, Spanner, Cloud SQL, Cloud Storage, Firestore, Memorystore)
- Planning for storage costs and performance
- Lifecycle management of data
3.2 Planning for using a data warehouse. Considerations include:
- Designing the data model
- Deciding the degree of data normalization
- Mapping business requirements
- Defining architecture to support data access patterns
3.3 Using a data lake. Considerations include:
- Managing the lake (configuring data discovery, access, and cost controls)
- Processing data
- Monitoring the data lake
3.4 Designing for a data mesh. Considerations include:
- Building a data mesh based on requirements by using Google Cloud tools (e.g., Dataplex, Data Catalog, BigQuery, Cloud Storage)
- Segmenting data for distributed team usage
- Building a federated governance model for distributed data systems
Domain 4 - Understand to prepare and use data for analysis (~15% of the exam)
4.1 Preparing data for visualization. Considerations include:
- Connecting to tools
- Precalculating fields
- BigQuery materialized views (view logic)
- Determining granularity of time data
- Troubleshooting poor performing queries
- Identity and Access Management (IAM) and Cloud Data Loss Prevention (Cloud DLP)
4.2 Sharing data. Considerations include:
● Defining rules to share data
● Publishing datasets
● Publishing reports and visualizations
● Analytics Hub
4.3 Exploring and analyzing data. Considerations include:
● Preparing data for feature engineering (training and serving machine learning models)
● Conducting data discovery
Section 5: Understand to maintain and automate data workloads (approx 18%)
5.1 Optimizing resources. Considerations include:
- Minimizing costs per required business need for data
- Ensuring that enough resources are available for business-critical data processes
- Deciding between persistent or job-based data clusters (e.g., Dataproc)
5.2 Designing automation and repeatability. Considerations include:
- Creating directed acyclic graphs (DAGs) for Cloud Composer
- Scheduling jobs in a repeatable way
5.3 Organizing workloads based on business requirements. Considerations include:
- Flex, on-demand, and flat rate slot pricing (index on flexibility or fixed capacity)
- Interactive or batch query jobs
5.4 Monitoring and troubleshooting processes. Considerations include:
- Observability of data processes (e.g., Cloud Monitoring, Cloud Logging, BigQuery admin panel)
- Monitoring planned usage
- Troubleshooting error messages, billing issues, and quotas
- Manage workloads, such as jobs, queries, and compute capacity (reservations)
5.5 Maintaining awareness of failures and mitigating impact. Considerations include:
- Designing system for fault tolerance and managing restarts
- Running jobs in multiple regions or zones
- Preparing for data corruption and missing data
- Data replication and failover (e.g., Cloud SQL, Redis clusters)
FAQs on Cloud Certified - Professional Data Engineer
1. What number of questions will there be in the exam?
As we update the certification exam over time to keep the current technology resultant the number of questions in an exam is subject to change. 40-60 questions are there in the most Microsoft Certification exams; although, the number can vary.
2. Is there any requirement to take an exam in English?
Microsoft Certification exams are offered in a variety of languages. Although, candidates can make a request for accommodation for an additional time those who must take the exam in English rather than in their native language. On a case-by-case basis approval for extra time is provided. Request test accommodations from Pearson VUE or Certiport.
3. What variety of questions appears on Microsoft Certification exams?
This level of information cannot be provided for each exam as Microsoft is constantly developing and pilot testing new question types. Although, you can review some possible exam formats and question types.
4. Is preparation for the performance-based exams are differently done from the other exams?
No. Regardless of the format of the question the skills measured remain the same. However, in the "Skills measured" section of the exam details page the knowledge and skills assessed in the exam are listed.
5. What does the score report look like?
A numeric score for overall exam performance is provided in the score report, status of pass/fail, and a bar chart showing performance in each skill area assessed in the exam. Using this information, the areas of strength and weakness of the candidates can be determined.
6. How the exam scores are calculated?
After the completion of your exam, the points you earned on each question are totalled and then compared with the cut score to determine whether the result is pass or fail.
7. Does Testprep Training offer Money Back Guarantee for the Exam Simulator?
Yes, we offer a 100% unconditional money back guarantee. In case you are not able to clear the exam for then, you can request for the full refund. Please note that we only refund the cost of product purchased from Testprep Training and not from the Microsoft Learning.
8. Is there any assistance from Testprep Training in terms of exam preparation?
Yes, Testprep Training offers email support for any certification related query while you are preparing for the exam using our practice exams. Your query will be handled by experts in due course.
9. Can we try the free test before purchasing the practice exam?
Yes, testprep training offers free practice tests for Cloud Certified - Professional Data Engineer which can be used before the final purchase for the complete test.
10. Do you provide any preparation guidance for this certification exam?
Yes, our experts frequently blog about the tips and tricks for exam preparation.
11. Do you offer any discount on the bulk purchase?
Yes, we offer nearly 50% discount for the order more than 10 products at a time. You can reach the testprep training Helpdesk for more details. The member of the support staff will respond as soon as possible.
12. For how long is the license valid after purchase?
Once purchased, the practice exams can be accessed for the lifetime.
13. Am I required to retake the exam? As the exams become updated with performance-based items.
No. The skills that are tested do not change; therefore, retesting is not necessary.
14. Do the exams with performance-based questions take longer to complete?
Yes. These exams may take longer to complete than exams that do not contain performance-based items. As performance-based questions are added to exams, you may see changes in the standardized exam times. No exam, however, will exceed 200 minutes, and the maximum seat time is 240 minutes.
15. What worth do the short answer questions have?
Most of the short answer questions are worth one point. In some cases, they might be worth more than one point. In these cases, we indicate within the question itself the number of points that it is worth.
For more FAQs
https://cloud.google.com/certification/faqs/#0
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