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Google Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and operationalizing data processing systems | 24% | - Data ingestion and integration
|
| Topic 2: Designing data processing systems | 22% | - Data architecture and storage design
|
| Topic 3: Operationalizing machine learning models | 26% | - ML pipeline integration
|
| Topic 4: Ensuring solution quality | 28% | - Security and governance
|
The Professional-Data-Engineer Exam and Our Materials: Full Details
You do not need to buy review material twice. If you fail the corresponding exam within 60 days of purchase, send us a scanned copy of your enrollment slip and your official Score Report PDF within two days of the exam date, and we will process a full refund within seven days of verification. Exclusions: exams taken within three days of purchase, candidate names that do not match the payer, and free or expired products. If you would rather switch tracks, we will exchange your product for two others of equal value at no cost.
The Google Certified Professional Data Engineer blueprint centers on these domains:
- Designing data processing systems (22%)
- Ensuring solution quality (28%)
- Building and operationalizing data processing systems (24%)
Additional domains complete the official outline, and our bank covers every one.
Registration goes through the official channels below:
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Currently, the Professional-Data-Engineer exam's passing score is Not publicly disclosed (scaled scoring system) and the registration fee is $200 USD. These figures belong to Google and can be revised, so confirm them on the official site before scheduling.
Google states the following prerequisites for the Google Certified Professional Data Engineer: No formal prerequisites required; recommended experience with data processing and Google Cloud Platform services.
For the authoritative details, see the official certification page.
Google recommends these official training resources:
- Google Cloud Data Engineering Learning Path
- Google Cloud Professional Data Engineer Course (Coursera)
Pair the course that fits your background with consistent question practice for the best results.
According to the latest exam information, the Professional-Data-Engineer exam contains Approximately 50–60 multiple choice and multiple select questions questions and lasts 120 minutes minutes. Simulating those conditions at home with the PC test engine is excellent preparation for the real environment.
Google Certified Professional Data Engineer Sample Questions:
Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?
- A. A processing time trigger
- B. An event time trigger
- C. The with Allowed Lateness method
- D. An hourly watermark
Correct Answer: A 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
The data analyst team at your company uses BigQuery for ad-hoc queries and scheduled SQL pipelines in a Google Cloud project with a slot reservation of 2000 slots. However, with the recent introduction of hundreds of new non time-sensitive SQL pipelines, the team is encountering frequent quota errors. You examine the logs and notice that approximately 1500 queries are being triggered concurrently during peak time. You need to resolve the concurrency issue. What should you do?
- A. Update SQL pipelines and ad-hoc queries to run as interactive query jobs.
- B. Increase the slot capacity of the project with baseline as 0 and maximum reservation size as
3000. - C. Update SQL pipelines to run as a batch query, and run ad-hoc queries as interactive query jobs.
- D. Increase the slot capacity of the project with baseline as 2000 and maximum reservation size as
3000.
Correct Answer: C 🗳️
You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?
- A. Add a new column called FullName to the Users table. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
- B. Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
- C. Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
- D. Use BigQuery to export the data for the table to a CSV file. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullName. Run a BigQuery load job to load the new CSV file into BigQuery.
Correct Answer: B 🗳️
What are the minimum permissions needed for a service account used with Google Dataproc?
- A. Execute to Google Cloud Storage; execute to Google Cloud Logging
- B. Write to Google Cloud Storage; read to Google Cloud Logging
- C. Read and write to Google Cloud Storage; write to Google Cloud Logging
- D. Execute to Google Cloud Storage; write to Google Cloud Logging
Correct Answer: C 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
You are a head of BI at a large enterprise company with multiple business units that each have different priorities and budgets. You use on-demand pricing for BigQuery with a quota of 2K concurrent on-demand slots per project. Users at your organization sometimes don't get slots to execute their query and you need to correct this. You'd like to avoid introducing new projects to your account. What should you do?
- A. Increase the amount of concurrent slots per project at the Quotas page at the Cloud Console.
- B. Create an additional project to overcome the 2K on-demand per-project quota.
- C. Convert your batch BQ queries into interactive BQ queries.
- D. Switch to flat-rate pricing and establish a hierarchical priority model for your projects.
Correct Answer: D 🗳️
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