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Course Outline
Introduction to Power BI in a Financial Context
- Exploring the Power BI ecosystem
- Identifying data types and essential features for financial analysis
- Reviewing the reporting requirements for payroll and cash flow
Data Sources and Modeling
- Importing payroll and cash flow data from Excel or CSV files
- Constructing data models that incorporate relationships and calculated columns
- Managing time intelligence for payroll cycles and monthly trends
Cash Flow Dashboards
- Visualizing inflows, outflows, and cash positions over time
- Conducting variance analysis and comparing forecasts
- Designing KPI cards, line charts, and waterfall charts
Payroll Reporting with Power BI
- Organizing payroll datasets covering earnings, benefits, and taxes
- Creating reports segmented by department, location, or employee category
- Detecting payroll trends, anomalies, and underlying cost factors
DAX for Financial Computations
- Applying basic DAX for cash flow metrics (e.g., net cash, rolling balances)
- Defining payroll-specific measures such as total compensation and tax ratios
- Utilizing DAX for cumulative and monthly breakdowns
Automating and Sharing Reports
- Publishing dashboards to the Power BI Service
- Configuring data refresh schedules and report subscriptions
- Securing report access for finance and HR teams
Best Practices and Case Studies
- Designing clear and insightful financial dashboards
- Modeling cash flow scenarios using what-if parameters
- Case study: Comprehensive payroll overview with drill-down capability to the employee level
Summary and Next Steps
Requirements
- A fundamental grasp of financial and payroll principles
- Proficiency with Microsoft Excel
Target Audience
- Finance professionals engaged in payroll and cash flow reporting
- HR analysts and payroll administrators
- Business analysts and Power BI users 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
