exam

Cert Prep: Microsoft Power BI Data Analyst (PL-300)

Hone your skills by practicing under real exam conditions.

Duration: Up to 1 hour and 40 minutes

Start

Timed examYou have 1h 40m to answer 40 questions in one session.

Navigate through questionsYou can mark questions to review later and navigate freely through the exam at any time

Minimum scoreYou must achieve the required scores for each topic to pass the exam.

Overview

Welcome to the preparation exam for Microsoft's PL-300: Microsoft Power BI Data Analyst exam.

This prep exam has the same number of multiple-choice questions (40) as the Microsoft Power BI Data Analyst exam, with the same allotted time for completion (100 minutes). Like the actual exam, some questions have one correct answer, while others require you to choose two or three correct answers.

The questions on this exam focus on the four domains of Microsoft Power BI knowledge listed below:

Prepare the data
Model the data
Visualize and analyze the data
Deploy and maintain assets

Each domain has the same level of emphasis as it will on the official exam.

In order to pass this prep exam, you will need both of the following:

A minimum score of 70 percent on the overall exam
A minimum score of 35 percent on each exam domain

Feedback:

Please contact us at platformsupport@qa.com if you have any questions or want to share your thoughts about the exam.

How to

You can spend as long as you wish on any particular question but must budget your time to complete all the questions. Any questions not completed in the allotted time are scored as incorrect.

You can change your answers or skip questions during the exam session. Use the Review later button to highlight questions you want to revisit. Use the Previous and Next buttons to navigate the questions.

You end your exam session by submitting your exam for a score or discarding it.

Exam UUID

Sessions

Results

You haven’t attempted this exam yet.

Topic

Required score

Exam overall

70%

Deploy and Maintain Assets

35%

Model the Data

35%

Prepare the Data

35%

Visualize and Analyze the Data

35%