Analyzing Data with Microsoft Power BI (DA-100) Practice Exam

The Analyzing Data with Microsoft Power BI (DA-100) exam is designed for individuals who want to validate their skills in data analysis and visualization using Power BI. The certification assess your skills to prepare data, model it, visualize it, and deploy reports and dashboards effectively. The Microsoft Power BI focuses on creating insightful business intelligence solutions for helping in decision-making. The DA-100 certification exam validates your skills in transforming raw data into actionable insights, crucial for organization using data-driven strategies.
Why is Analyzing Data with Microsoft Power BI (DA-100) important?

• Recognition of your proficiency as data analyst in using Power BI for data analysis.
• Boosts  opportunities for roles that require expertise in business intelligence and data visualization.
• Validates your skills to transform data into meaningful insights through effective visualization techniques.
• Places you ahead of others in the growing need for professionals skilled in data analytics and reporting.
• Prepares candidates to deliver data-driven insights that support strategic business decisions.

Who should take the Analyzing Data with Microsoft Power BI (DA-100) Exam?

• Data Analyst
• Business Intelligence Analyst
• Data Scientist
• Reporting Analyst
• Analytics Consultant

Candidates taking the certification exam on the Analyzing Data with Microsoft Power BI (DA-100) is evaluated for the following skills:

• Preparing data for analysis, including data cleansing and transformation.
• Creating and managing data models.
• Designing and building effective reports and dashboards.
• Utilizing DAX (Data Analysis Expressions) for advanced data manipulation.
• Sharing and collaborating on Power BI reports and dashboards.

Analyzing Data with Microsoft Power BI (DA-100) Certification Course Outline
The Analyzing Data with Microsoft Power BI (DA-100) Certification covers the following topics -

1. Prepare the Data (20-25%)
1.1 Get data from different data sources
1.2 Profile the data
1.3 Clean, transform and load the data

2. Model the Data (25-30%)
2.1 Design a data model
2.2 Develop a data model
2.3 Create measures by using DAX
2.4 Optimize model performance

3. Visualize the Data (20-25%)
3.1 Create reports
3.2 Create dashboards
3.3 Enrich reports for usability

4. Analyze the Data (10-15%)
4.1 Enhance reports to expose insights
4.2 Perform advanced analysis

5. Deploy and Maintain Deliverables (10-15%)
5.1 Manage datasets
5.2 Create and manage workspaces