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Microsoft Power BI Data Analyst Exam Certification Details:
| Exam Code | PL-300 |
| Sample Questions | Microsoft Power BI Data Analyst Sample Questions |
| Schedule Exam | Pearson VUE |
| Duration | 180 mins |
| Number of Questions | 40-60 |
| Books / Training | Course PL-300T00: Microsoft Power BI Data Analyst |
| Exam Price | $165 (USD) |
| Passing Score | 700 / 1000 |
| Exam Name | Microsoft Certified - Power BI Data Analyst Associate |
Learn more about the exam
The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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Microsoft Power BI Data Analyst Certification Exam Reference
Microsoft PL-300 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prepare the data | 25-30% | - Profile and clean data
|
| Visualize and analyze data | 25-30% | - Create reports and dashboards
|
| Manage and secure Power BI | 15-20% | - Implement security and governance
|
| Model the data | 25-30% | - Optimize model performance
|






