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- Total Questions: 77
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Google GCP-DE Exam Overview:
| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Professional Data Engineer |
| Exam Number: | GCP-DE |
| Exam Price: | $200 USD |
| Available Languages: | Japanese, English |
| Exam Format: | Multiple select, Multiple choice |
| Related Certifications: | Google Cloud Certified Professional Data Engineer |
| Real Exam Qty: | 50-60 |
| Passing Score: | Not publicly disclosed |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 120 minutes |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | No formal prerequisites. Google recommends 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud. |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-engineer |
Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Ensuring solution quality | 20%-25% | - Security and compliance
|
| Building and operationalizing data processing systems | 28%-33% | - Building data processing systems
|
| Managing and optimizing solutions | 20%-25% | - Reliability and scalability
|
| Designing data processing systems | 22%-27% | - Designing for data ingestion
|
Google GCP-DE Exam — Answers to Your Questions
The Google Data Engineer (exam code GCP-DE) is the exam you pass to earn the Google Cloud Certified certification, a credential at the Professional level. It is also connected with related credentials such as Google Cloud Certified Professional Data Engineer. If you are mapping out a certification path with Google, this exam is a milestone worth planning around.
The GCP-DE exam includes 50-60 questions, and you have 120 minutes to complete them. With that many questions on the clock, pacing is part of the challenge: divide your time into rough blocks as you go, and flag the items that stall you so you can circle back at the end instead of burning minutes on a single question. A week or two before your exam date, sit at least one full timed session in the 2Pass4sure test engine under the same time limit, so the pace feels familiar rather than frantic on the day.
You need Not publicly disclosed to pass the GCP-DE exam, and the official registration fee is $200 USD. That fee is due again in full for every retake, which makes thorough preparation the cheaper investment by far. Before you book your seat, test yourself with the 2Pass4sure practice questions until you are scoring comfortably above the passing mark on a consistent basis — it is the simplest way to avoid paying for the same exam twice.
No formal prerequisites. Google recommends 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud.
Eligibility rules can be adjusted by Google over time, so before you register, confirm the current requirements on the official exam page: view the official GCP-DE exam information.
Yes. 2Pass4sure offers a free PDF demo of the GCP-DE practice questions, so you can judge the quality of the material firsthand before paying anything. Every purchase also includes 365 days of free updates — if Google changes the exam during that year, your material changes with it. And when the free update period expires, you can extend it at a 50% discount from within your member zone.
Every GCP-DE purchase at 2Pass4sure is backed by a 100% Money Back Guarantee: if you take the corresponding exam within 60 days of your purchase and do not pass, you can apply for a full refund. The guarantee has clear conditions — it does not apply if you sit the exam within 3 days of purchase, if you downloaded the material but never actually took the exam, or to free materials and expired orders, and the candidate name must match the payer name. To file a claim, send a scan of your exam enrollment slip together with your official Score Report PDF within 2 days of the exam; claims are processed within 7 days. If you would rather not take a refund, you can exchange the product instead and receive two additional exam preparation products of equal value for free, while your original product keeps its update service. Delivery itself is instant: your material is available for download right after payment and is also sent to your email within one minute — if it has not arrived within 2 hours, contact our customer service. There is no limit on how many computers you can install it on.
The official Google Data Engineer outline divides the exam content into 4 main domains. The first three are:
- Managing and optimizing solutions — 20%-25%
- Building and operationalizing data processing systems — 28%-33%
- Ensuring solution quality — 20%-25%
That is only the headline view — scroll back up to the Exam Topics section on this page for the complete domain-by-domain breakdown before you plan your study schedule.
Google Data Engineer Sample Questions:
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn't like to eat
The user account information: Name, address, preferred meal times
The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schem a. Which Google Cloud Platform product should you use?
- A. BigQuery
- B. Cloud SQL
- C. Cloud Datastore
- D. Cloud Bigtable
You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?
- A. Locate the bottleneck and adjust cluster resources.
- B. Use the diagnose command to generate an operational output archiv
- C. Monitor the job system lag with Stackdrive
- D. Use Cloud Dataproc to run your transformation
- E. Use Cloud Dataproc to run your transformation
- F. Use Cloud Dataflow to run your transformation
- G. Configure the job to use non-default Compute Engine machine types when needed.
- H. Use the default autoscaling setting for worker instances.
- I. Use Cloud Dataflow to run your transformation
- J. Monitor CPU utilization for the cluste
- K. Monitor the total execution time for a sampling of job
- L. Resize the number of worker nodes in your cluster via the command line.
You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?
- A. Write an Apache Beam pipeline that creates a BigQuery table per data
- B. Partition the tables by a column containing a TIMESTAMP or DATE Type.
- C. Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
- D. Re-create the tables using DD
- E. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
- F. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?
- A. Cloud AutoML Natural Language
- B. Cloud Natural Language API
- C. Dialogflow Enterprise Edition
- D. Cloud Speech-to-Text API
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?
- A. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
- B. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
- C. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
- D. Create an authorized view in BigQuery to restrict access to tables with sensitive data.
- E. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
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