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Microsoft DA-100 (Analyzing Data with Microsoft Power BI) Certification Exam is a comprehensive certification exam that measures an individual's ability to analyze data using Microsoft Power BI. Preparing for DA-100 exam requires a thorough understanding of Power BI and its various features, as well as experience working with data sources and transforming data. Earning this certification can help you advance your career in data analysis and visualization and increase your earning potential.
The Microsoft DA-100 exam (Analyzing Data with Microsoft Power BI) is intended for data analysts and is the only test required to obtain the Microsoft Certified: Data Analyst Associate certificate.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100
Career Opportunities and Pay
After getting through with DA-100 exam and earning the Microsoft Certified: Data Analyst Associate certification, you will be able to offer more for big business companies that need more analytical power that Excel cannot provide. This opens up multiple job opportunities with decent average annual salaries. Below are some of them as covered by Payscale:
- Web Data Analyst: $67k.
- Data Analyst: $61k;
- IT Operation Analyst: $56k;
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Microsoft DA-100 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Prepare the data | 20-25% | - Get data from data sources
- 1. Select appropriate storage modes (Import, DirectQuery, Composite)
- 2. Connect to data sources (files, databases, cloud services)
- Clean and transform data
- 1. Use Power Query Editor for data shaping
- 2. Handle missing, duplicate, and inconsistent data
|
| Visualize the data | 25-30% | - Create reports
- 1. Design interactive reports in Power BI Desktop
- 2. Use visuals such as charts, maps, and tables
- Enhance reports
- 1. Apply filters, slicers, and drill-through
- 2. Use bookmarks and navigation elements
|
| Analyze the data | 10-15% | - Analyze data patterns
- 1. Identify trends and outliers
- 2. Use AI visuals and quick insights
- Perform advanced analytics
- 1. Use DAX time intelligence functions
- 2. Apply statistical measures in reports
|
| Model the data | 25-30% | - Create calculated columns and measures
- 1. Optimize model performance
- 2. Use DAX for calculations
- Design data models
- 1. Create relationships between tables
- 2. Design star and snowflake schemas
|
| Deploy and maintain deliverables | 10-15% | - Manage workspaces and datasets
- 1. Configure dataset refresh schedules
- 2. Publish reports to Power BI Service
- Secure and share content
- 1. Implement row-level security (RLS)
- 2. Share dashboards with users and groups
|