Microsoft DA-100 Deutsch

Certification Path

After acquiring the Microsoft Certified: Data Analyst Associate certification, you are competent to go further and broaden your expertise in the Microsoft BI platform. Although this certificate is not a direct requirement for other BI-related validations, it will sure help you get started with the higher-level certifications like the Microsoft Certified: Dynamics 365 + Power Platform Solution Architect Expert.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

About Exam DA-100: Analyzing Data with Microsoft Power BI

The Microsoft DA-100 test is for those individuals who have at least some experience in working with Power Bi although it is not a strict requirement but a recommendation. In addition, the applicant should have some experience in the concepts of scaling data models, data visualizations, data cleaning, and data processing. When it comes to the test details, DA-100 exam is available in English, Chinese (Simplified), Korean, Japanese and will require $165 for registration. The registered candidate can use the Pearson VUE platform for scheduling an exam. In the final test, individuals will experience around 40-60 items that will have to be solved in 3 hours.

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2. Data Model (25-30%):

The main domains of this section are:

• Creation of measures with DAX: The applicants should be able to utilize DAX in building multifaceted measures, use CALCULATE to maneuver filters, and utilize the fundamental statistical functions for enhancing data. This domain also requires their skills in creating semi-additive measures and implementing Time Intelligence with DAX.
• Data model development: This objective requires one’s ability to create hierarchies, calculated tables, and calculated columns. It also covers your skills in establishing Q&A features, implementing row-level security functions, and applying security filtering and cross-filter direction.
• Model performance optimization: This module will measure your competence in enhancing cardinality levels through changing data types and summarization. It will also evaluate your skills in eliminating unnecessary columns and rows, creating and managing aggregations, and identifying poorly performing visuals, measures, and relationships.
• Data model design: The learners need to have competence in defining tables, role-playing dimensions, quick measures, and cross-filter direction & relationship cardinality. The topic also requires their skills in designing a data model to fulfill the performance prerequisites, creating common data tables, and solving many-to-many relationships.