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Professional-Data-Engineer Exam Dumps : Google Professional Data Engineer Exam

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Google Professional-Data-Engineer Exam Dumps FAQs

Q. # 1: What is the Google Professional-Data-Engineer Exam?

The Google Professional-Data-Engineer certification validates your ability to design, build, operationalize, secure, and monitor data processing systems on Google Cloud.

Q. # 2: Who should take the Google Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is targeted at data engineers, data analysts, machine learning engineers, and cloud architects who want to demonstrate their expertise in managing data solutions on Google Cloud Platform.

Q. # 3: What topics are covered in the Google Professional-Data-Engineer Exam?

The exam covers:

  • Designing data processing systems

  • Building and operationalizing data pipelines

  • Managing data solutions

  • Ensuring solution quality

  • Leveraging machine learning models

Q. # 4: What is the format of the Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is multiple-choice and multiple-select, delivered online or at a testing center via Kryterion.

Q. # 5: Are there any prerequisites for the Professional-Data-Engineer Exam?

There are no formal prerequisites, but Google recommends 3+ years of industry experience, including 1+ year with Google Cloud.

Q. # 6: What is the difference between Google Professional-Data-Engineer and Associate-Cloud-Engineer Exam?

The Google Professional Data Engineer and Associate Cloud Engineer exams differ mainly in focus, difficulty level, and job roles.

  • The Associate Cloud Engineer certification is entry-level, designed for professionals who deploy, manage, and maintain applications on Google Cloud Platform (GCP). It validates general cloud operations, setup, and configuration skills.
  • The Professional Data Engineer, on the other hand, is an advanced-level certification focused on designing, building, and managing data processing systems, data analytics, and machine learning models using GCP services like BigQuery, Dataflow, Dataproc, and Pub/Sub.

Q. # 7: What is the difficulty level of the Professional-Data-Engineer Exam?

The Professional-Data-Engineer exam is considered moderate to advanced, requiring hands-on experience with GCP data services and machine learning workflows.

Q. # 8: Where can I find Google Professional-Data-Engineer exam dumps and practice tests?

Visit CertsTopics for verified Professional-Data-Engineer exam dumps, questions and answers, and practice tests that mirror the real exam and come with a success guarantee.

Q. # 9: Is there a success guarantee with CertsTopics materials?

Yes, CertsTopics provides a success guarantee with regularly updated Professional-Data-Engineer dumps material crafted by certified professionals to help you pass on your first attempt.

Google Professional Data Engineer Exam Questions and Answers

Question 1

Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow. Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour.

The data scientists have written the following code to read the data for a new key features in the logs.

BigQueryIO.Read

.named(“ReadLogData”)

.from(“clouddataflow-readonly:samples.log_data”)

You want to improve the performance of this data read. What should you do?

Options:

A.

Specify the TableReference object in the code.

B.

Use .fromQuery operation to read specific fields from the table.

C.

Use of both the Google BigQuery TableSchema and TableFieldSchema classes.

D.

Call a transform that returns TableRow objects, where each element in the PCollexction represents a single row in the table.

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Question 2

You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patientrecords. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources. How should you adjust the database design?

Options:

A.

Add capacity (memory and disk space) to the database server by the order of 200.

B.

Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.

C.

Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.

D.

Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.

Question 3

Business owners at your company have given you a database of bank transactions. Each row contains the user ID, transaction type, transaction location, and transaction amount. They ask you to investigate what type of machine learning can be applied to the data. Which three machine learning applications can you use? (Choose three.)

Options:

A.

Supervised learning to determine which transactions are most likely to be fraudulent.

B.

Unsupervised learning to determine which transactions are most likely to be fraudulent.

C.

Clustering to divide the transactions into N categories based on feature similarity.

D.

Supervised learning to predict the location of a transaction.

E.

Reinforcement learning to predict the location of a transaction.

F.

Unsupervised learning to predict the location of a transaction.