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Course Outline
Introduction to Power BI in Finance
- Exploring the Power BI ecosystem
- Key data types and features essential for financial analysis
- Overview of specific payroll and cash flow reporting requirements
Data Sources and Modeling
- Importing payroll and cash flow data from Excel or CSV files
- Constructing data models using relationships and calculated columns
- Applying time intelligence to manage payroll cycles and monthly trends
Cash Flow Dashboards
- Visualizing inflows, outflows, and cash positions over time
- Conducting variance analysis and comparing forecasts
- Implementing KPI cards, line charts, and waterfall charts
Payroll Reporting in Power BI
- Organizing payroll datasets including earnings, benefits, and taxes
- Generating reports segmented by department, location, or employee type
- Detecting payroll trends, anomalies, and primary cost drivers
DAX for Financial Calculations
- Applying basic DAX for cash flow metrics (e.g., net cash, rolling balances)
- Defining payroll-specific measures such as total compensation and tax ratios
- Leveraging DAX for cumulative and monthly breakdowns
Report Automation and Sharing
- Publishing dashboards to the Power BI Service
- Configuring data refresh schedules and report subscriptions
- Securely sharing reports with finance and HR teams
Best Practices and Use Case Walkthroughs
- Designing intuitive and insightful financial dashboards
- Modeling cash flow scenarios using what-if parameters
- Case study: Comprehensive payroll overview with employee-level drill-down capabilities
Summary and Next Steps
Requirements
- Fundamental knowledge of financial and payroll concepts
- Proficiency with Microsoft Excel
Target Audience
- Finance professionals responsible for payroll and cash flow reporting
- HR analysts and payroll managers
- Business analysts and Power BI users operating within finance teams
14 Hours
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
engagement with the attendees
