Microsoft DA-100 : Analyzing Data with Microsoft Power BI

Ideal Audience and Required Skills

DA-100 is intended for data analysts who use MS Power BI to enhance the value of the data their organization holds. These professionals are responsible for polishing and transforming data, creating expandable data models, and performing data visualizations that can be interpreted and analyzed to withdraw critical information. Data analysts also work alongside other stakeholders of the business to provide relevant data according to their company’s requirements. Thus, a strong prior understanding of both cloud & on-premises data processing and data repositories is also required by those specialists who are going to take test DA-100.

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

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What is the Microsoft DA-100 exam?

The Microsoft DA-100 exam is available in English, Japanese, Simplified Chinese, and Korean. The learners can expect 40-60 questions in the delivery of the test with the time allowance of 180 minutes. Depending on where they are taking the exam, it is available as a proctored option or at any Pearson VUE testing center. The candidates can register for this certification exam with Pearson VUE and pay the fee of $165 to schedule it. This price is established for the individuals from the United States. If you sit for the test in another country, you should check the actual price on the official website.

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Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Model the data

The following will be discussed in MICROSOFT DA-100 exam dumps:

• Resolve many-to-many relationships
• Improve cardinality levels by changing data types
• Create semi-additive measures
• Set up the Q&A feature
• Define quick measures
• Implement row-level security roles
• Create hierarchies
• Flatten out a parent-child hierarchy
• Define the appropriate level of data granularity
• Use DAX to build complex measures
• Replace numeric columns with measures
• Configure table and column properties
• Improve cardinality levels through summarization
• Design the data model to meet performance requirements
• Create and manage aggregations
• Create calculated tables
• Identify poorly performing measures, relationships, and visuals
• Use basic statistical functions to enhance data
• Develop a data model
• Define role-playing dimensions
• Define a relationship's cardinality and cross-filter direction
• Create calculated columns
• Create measures by using DAX
• Apply cross-filter direction and security filtering
• Implement Time Intelligence using DAX
• Design a data model
• Use CALCULATE to manipulate filters
• Remove unnecessary rows and columns
• Create a common date table
• Define the tables
• Optimize model performance

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