ACPM: Business Data Analysis in Finance

Microsoft Power BI for Finance Professionals

Lessons

1.1. Fundamentals of Data Analysis in Microsoft Power BI

• What is data analysis?
• Principles of practical data analysis
  Introduction to Microsoft Power BI and how to use it

1.2. Basics of Budgeting in Power BI

• Advantages of digital budgeting
• Budget hierarchy and linking different budgets
• Logic of building budget dashboards

1.3. Case Study: Budget Request

• Creating and analysing a business budget
• Selecting metrics and dimensions, performing calculations
• Providing recommendations for key budget performance indicators

1.4. Case Study: Plan vs Actual for the First Half-Year

• Analysing business performance by areas (staff, sales, finance)
• Selecting metrics and dimensions, performing calculations
• Commenting on and explaining key business activities

1.5. Case Study: 5-Year Business Plan

• Planning business operations for 5 years across key areas (sales, revenue, net profit)
• Selecting metrics and dimensions, performing calculations
• Building dashboards for quick strategic assessment

Digital Transformation for CFOs

Lessons

2.1. Fundamentals of the Digital Economy

• The essence of the digital economy and how it differs from the real economy
• Success factors and drawbacks of the digital economy
• How the digital economy is transforming finance and how finance professionals can adapt

2.2. The CFO’s Digital Transformation

• Differences between a traditional CFO and a digital CFO
• How digitalisation impacts CFO responsibilities
• Core skills for CFO transformation and common obstacles

2.3. Case Study: Cash Flow Budget

• Analysing cash flow budgets (direction, month, type of activity)
• Selecting metrics, performing calculations
• Identifying cash gaps

2.4. Case Study: Accounts Receivable

• Analysing accounts receivable (amount, debtor, quarter)
• Selecting metrics, performing calculations
• Supporting debtor management (who is at risk and who is not?)

2.5. Case Study: Sales Analysis

• Analysing product sales performance (customer, revenue, discount rate)
• Selecting metrics, performing calculations
• Improving sales (why offer bigger discounts to some customers?)

Modern Financial Visualisation with Microsoft Power BI

Lessons

3.1. Finance in the Art of Visualisation

• Charts and dashboards as the foundation of modern visualisation
• Best chart types for financial use
• Techniques for improving charts

3.2. How Modern Visualisation is Built in Power BI

• Data analysis techniques for visualisation
• Using calculations and measures in visualisations
• Enhancing clarity and efficiency with six key techniques

3.3. Case Study: Online Advertising

• Analysing online advertising effectiveness (countries, devices)
• Selecting metrics and dimensions, performing calculations and groupings
• Reducing advertising costs (why stop selling to Norway?)

3.4. Case Study: Car Sales Specifics

• Analysing car sales performance (colour, model)
• Selecting metrics and dimensions, performing calculations and groupings
• Improving car sales (why too many colours is a bad thing?)

3.5. Case Study: Working with Walmart

• Analysing product sales performance at Walmart (category, price)
• Selecting metrics and dimensions, performing calculations and groupings
• Deciding what to sell at Walmart (why are we selling the cheapest items?)

Planning for Finance Professionals in the Digital Age

Lessons

4.1. Planning for Finance Professionals in the Digital Age

• Goals and criteria of modern planning
• Key aspects of financial plans
• Can digital tools support traditional planning?

4.2. Transformation of Planning Tasks in the Digital Era

• Evolving planning tasks
• Dynamic integration of plans and budgets
• Data culture among finance professionals

4.3. Case Study: Online Sales Planning

• Analysing sales performance (countries, sale price, cost price)
• Selecting metrics and dimensions, performing calculations and groupings
• Reviewing sales and production plans (understanding where and how much to sell)

4.4. Case Study: Cost Planning

• Modelling sales plans, revenue, variable and fixed costs
• Setting up calculations
• Graphically optimising net profit through cost management

4.5. Case Study: Dynamic Planning in Retail

• Modelling sales under uncertainty
• Selecting and configuring revenue and profit drivers
• Evaluating discount levels and stock reduction thresholds (stress scenarios)

Practical Application of Business Analysis

Lessons

5.1. Practical Business Analysis

• What is practical business analysis?
• Why is it important for business?
• Key knowledge areas in practical business analysis

5.2. Game-Based Case Study: Online Advertising Analytics

• Reviewing real data
• Selecting numerical metrics for comparison and discussion
• Analysing advertising effectiveness using charts and maps

5.3. Case Study: Business Analytics in Hospitality

• Reviewing real data: specifics of the hospitality industry
• Selecting numerical metrics and analysing business growth
• Making data-driven decisions – to close or not?

5.4. Case Study: Real Estate Agent Analytics

• Understanding the abundance of data in real estate
• Selecting metrics and dimensions, identifying key points
• Detailed review of products and sales geography

5.5. Case Study: Medical Clinic Analytics

• How to analyse data in healthcare – are there specifics?
• Selecting metrics and dimensions, understanding key differences
• Analysing doctor workloads, identifying top performers, and providing recommendations on working hours and staff training

Final Online Exam