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Duration 7 hours
Course Outline
Introduction to PL-300 Certification
- Exam objectives and structural overview
- Assessed skills and competency domains
- Recommended preparation resources and study approaches
Data Preparation for Financial Reporting
- Extracting and refining data via Power Query
- Merging multiple financial data sources
- Managing time-based and transactional data
Financial Data Modeling
- Architecting data models for financial analysis
- Establishing relationships and hierarchies (accounts, cost centers, departments)
- Implementing measures for tracking revenue, costs, and profit
Developing Financial KPIs and Calculations
- Key financial metrics: ROI, variance, margin, and growth rate
- Leveraging DAX for year-to-date and rolling calculations
- Engineering custom KPIs for business performance evaluation
Visualizing Financial Insights
- Constructing executive dashboards and scorecards
- Applying conditional formatting and key influencers visuals
- Generating visuals for variance, trend, and cash flow analysis
Exam Preparation and Practice
- Analyzing common PL-300 questions and scenarios
- Case-based exercises mirroring real exam topics
- Final review: best practices and test-taking strategies
Hands-on Project: Financial Dashboard Simulation
- Developing a comprehensive financial analysis report for a sample company
- Synthesizing data modeling, measures, and visuals
- Peer review and feedback sessions
Conclusion and Next Steps
Requirements
- Familiarity with Power BI data modeling and visualization techniques
- Practical experience handling financial data or reports
- Foundational knowledge of DAX and Excel formulas
Target Audience
- Financial analysts preparing for the Microsoft PL-300 certification
- Business intelligence specialists dedicated to financial reporting
- Accountants and finance managers leveraging Power BI for data-driven insights
Testimonials (2)
How to use relationships in Power BIand the differences between columns and measurements
LEUNG Chun Hei - HAESL
Course - Advanced Power BI: Data Modeling, DAX, and Enhanced Analytics
Method of training.
