PL-300
Microsoft Power BI Data Analyst
Certification Overview
Microsoft's Power BI certification covering data modeling, DAX, and visualization best practices. The 100-minute exam has 60 questions (multiple-choice, case studies, drag-drop) requiring 700/1000 to pass. Renewable via free Microsoft Learn assessment.
The Microsoft Power BI Data Analyst (PL-300) is a globally recognized benchmark designed for professionals aiming to prove their expertise in data. In today's competitive landscape, this certification acts as a critical signal to employers regarding your technical proficiency and commitment to the field.
Primary Impact
- Higher salary ceiling in Data roles
- Validated expertise at the enterprise level
Market Signal
Ranked as a Top Data Credential for 2026, holding the PL-300 significantly reduces the time-to-hire for senior positions.
Market Outlook
We monitor job market volume in real-time to provide the most accurate demand forecasting for your career.
Market Sentiment
There are currently 460 open roles in the US requiring this specific certification.
Tracking period: 12 Weeks
Job data provided by Adzuna
Is PL-300 right for you?
Don't make a blind decision. Compare PL-300 against similar certifications to find the best ROI for your specific career path.
PL-300 vs AWS-DEA
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Maintenance & Recognition
Renewal Requirements
Industry Recognition
Proctoring Options
Path to Excellence
Everything you need to successfully navigate the PL-300 certification journey.
01 Entry Requirements
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Data Analysis Skills
Knowledge of data modeling, DAX, and Power BI Desktop.
02 The Process
Power BI Modeling
Learn to transform and load data, and build complex relationships.
DAX Mastery
Master complex measures and filters to uncover deep data insights.
Pass PL-300 Exam
Pass the Microsoft Power BI Data Analyst Associate exam.
PL-300 Complete Study Guide
Strategic study plan, exam breakdown, and career acceleration tactics — everything you need to pass.
Ready to Get Certified?
Start your PL-300 certification journey today and open doors to new opportunities in data.