Microsoft Power BI DA-100 EXAM: Advanced Practice Exams 2022

Microsoft Power BI DA-100 EXAM: Advanced Practice Exams 2022

Microsoft Power BI DA-100 EXAM: Advanced Practice Exams 2022

Practice DA-100 Power BI exam. 2x Full-Length Practice Tests with detailed explanations! Pass DA100 with confidence!

Language: english

Note: 0/5 (0 notes) 1,037 students

Instructor(s): Zouan Sanaa


Are you planning to become a Microsoft Certified Data Analyst Associate?

This practice test will break down all the concepts covered in the Exam DA-100, giving you real know-how about analyzing and visualizing data in the Power BI platform.

But mostly: this practice test will prepare you to deal with the design of the questions for the Exam DA-100.

This is a key point: no matter how hard you study Microsoft Power BI documentation. If you plan to get the Power BI Certification you need to work by advanced usage of Power BI platform on practical business cases. This will really measure your Data Analysis skills.

Thus, in this test, you will not find just theory questions. You will achieve a proven experience in facing businesslike issues, needed to pass the Exam DA-100, and become a Microsoft Certified Data Analyst Associate.

To take the exam DA-100 and, mostly, to use profitably Power BI features, you need to gain experience in six knowledge areas:

  • Microsoft DAX language;

  • Microsoft Power Query features;

  • Data Modeling in Power BI;

  • Data Visualization in Power BI;

  • Manage Publishing and Sharing Power BI contents;

  • Manage Power BI Administration settings.

Who this course is for?

Professional Data Analysts, Junior Data Analysts, and anyone who manages data. No matters what is your professional role, if you want to experience all the features provided by Microsoft Power BI: it is the current all-in-one market leader solution in Analyzing and Visualizing Data. Taking the DA-100 exam accredits you as a Microsoft Data Analyst Associate. This is an advanced career pass that certifies your skills in designing and building data models, cleaning and transforming data, and using advanced analytic capabilities to enhance data-driven strategy inside profit and no-profit organizations.

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