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Google Professional-Data-Engineer Exam With Confidence Using Practice Dumps

Exam Code:
Professional-Data-Engineer
Exam Name:
Google Professional Data Engineer Exam
Certification:
Vendor:
Questions:
376
Last Updated:
Aug 27, 2025
Exam Status:
Stable
Google Professional-Data-Engineer

Professional-Data-Engineer: Google Cloud Certified Exam 2025 Study Guide Pdf and Test Engine

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Google Professional Data Engineer Exam Questions and Answers

Question 1

Given the record streams MJTelco is interested in ingesting per day, they are concerned about the cost of Google BigQuery increasing. MJTelco asks you to provide a design solution. They require a single large data table called tracking_table. Additionally, they want to minimize the cost of daily queries while performing fine-grained analysis of each day’s events. They also want to use streaming ingestion. What should you do?

Options:

A.

Create a table called tracking_table and include a DATE column.

B.

Create a partitioned table called tracking_table and include a TIMESTAMP column.

C.

Create sharded tables for each day following the pattern tracking_table_YYYYMMDD.

D.

Create a table called tracking_table with a TIMESTAMP column to represent the day.

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Question 2

The CUSTOM tier for Cloud Machine Learning Engine allows you to specify the number of which types of cluster nodes?

Options:

A.

Workers

B.

Masters, workers, and parameter servers

C.

Workers and parameter servers

D.

Parameter servers

Question 3

You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.

You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)

Options:

A.

Redis

B.

HBase

C.

MySQL

D.

MongoDB

E.

Cassandra

F.

HDFS with Hive