Introduction

This comprehensive program is designed to equip finance professionals with the skills to harness the full capabilities of Microsoft Power BI for data analysis, financial reporting, and decision-making. Participants will learn how to connect Power BI to various financial data sources, create insightful dashboards, and apply advanced analytics to support budgeting, forecasting, and performance monitoring. The program focuses on real-world finance scenarios, enabling participants to turn raw data into actionable insights that drive strategic decisions.

Target Audience

• Financial Analysts

• Accountants and Auditors

• Finance Managers and Controllers

• Budget and Cost Control Specialists

• CFOs and Finance Directors seeking analytical tools for decision-making

Objectives

By the end of this program, participants will be able to:

• Understand the fundamentals and interface of Power BI.

• Connect and transform financial data from multiple sources.

• Create interactive and dynamic finance-related dashboards.

• Apply DAX (Data Analysis Expressions) for financial calculations.

• Implement advanced analytics for budgeting, forecasting, and variance analysis.

• Automate and share financial reports with stakeholders securely.

Course Methodology

• Instructor-led demonstrations

• Hands-on practice using real-world financial datasets

• Group exercises and scenario-based assignments

• Q&A sessions and troubleshooting tips

Outline

Day 1 – Power BI Fundamentals for Finance

• Introduction to Business Intelligence and Power BI’s role in finance

• Navigating the Power BI Desktop interface

• Connecting to common finance data sources (Excel, CSV, databases, ERP exports)

• Import vs DirectQuery for financial data

• Understanding the Power Query Editor for cleaning and shaping financial data

• Practical Exercise: Importing and cleaning a Profit & Loss statement dataset

Day 2 – Data Modeling and Relationships

• Building a robust data model for financial reporting

• Understanding tables, fields, and data types

• Creating relationships between datasets (e.g., budget vs actuals, departmental breakdowns)

• Star schema vs snowflake schema in financial analytics

• Best practices for organizing financial data in Power BI

• Practical Exercise: Linking Actuals, Budgets, and Departmental data

Day 3 – DAX for Financial Calculations

• Introduction to DAX and its importance for finance analytics

• Creating calculated columns and measures

• Common DAX functions for finance: SUM, CALCULATE, FILTER, DIVIDE, DATE functions

• Time intelligence for month-to-date (MTD), quarter-to-date (QTD), and year-to-date (YTD) calculations

• Variance analysis (actual vs budget, year-over-year growth)

• Practical Exercise: Building financial KPIs using DAX

Day 4 – Creating Financial Dashboards and Reports

• Designing effective financial visuals (tables, matrices, waterfall charts, KPIs)

• Using slicers, filters, and drill-through for finance reports

• Conditional formatting for highlighting financial performance trends

• Creating dashboards for cash flow, profitability, and expense tracking

• Storytelling with data: best practices for finance presentations

• Practical Exercise: Creating an interactive departmental expense dashboard

Day 5 – Advanced Analytics, Automation, and Sharing

• Forecasting and trend analysis in Power BI

• Using “What-if” parameters for scenario planning in finance

• Automating data refresh for live financial dashboards

• Publishing and sharing reports securely within the organization

• Power BI Service vs Power BI Desktop: what finance professionals need to know

• Q&A, feedback, and next steps for applying Power BI in finance