This project presents an interactive Power BI executive dashboard built using Microsoft's Financial Sample dataset.
The objective was to transform transactional business data into a clear Business Intelligence solution that allows decision-makers to monitor company performance, explore product profitability, evaluate geographic and customer segment performance, and identify relevant business insights.
The final solution consists of three interconnected analytical pages:
- Executive Overview
- Product Analysis
- Market & Segment Analysis
The dashboard combines KPI monitoring, interactive filtering, DAX calculations, time analysis, product performance, geographic analysis, customer segmentation, and dynamic business insights.
The dashboard was designed to answer questions such as:
- How much revenue and profit is the company generating?
- What is the overall profit margin?
- Which countries generate the most sales and profit?
- Which products contribute the most revenue?
- Which products achieve the strongest margins?
- How do discounts relate to product profitability?
- Which customer segments generate the most revenue?
- Which segments are the most and least profitable?
- How does sales performance evolve over time?
- What key insights should executives monitor?
- Power BI Desktop
- Power Query
- DAX
- Data Modeling
- Date Table Modeling
- Time Intelligence
- KPI Design
- Data Visualization
- Interactive Filtering
- Business Intelligence
- Business Analysis
- Git
- GitHub
The project uses the Microsoft Financial Sample Dataset, an official sample dataset designed for Power BI analysis.
The dataset contains approximately 700 records covering:
- Countries
- Customer segments
- Products
- Units sold
- Manufacturing prices
- Sale prices
- Gross sales
- Discounts
- Revenue
- COGS
- Profit
- Dates
The available data covers part of 2013 and the full 2014 calendar year.
Because 2013 contains only a partial year, year-over-year comparisons were not used as headline executive KPIs in order to avoid misleading comparisons between incomplete and complete periods.
A dedicated Date table was created to support reliable time-based analysis.
The model includes:
financials– main transactional tableDateTable– dedicated calendar table- One-to-many relationship between
DateTable[Date]andfinancials[Date] - Single-direction filtering from the Date table to the transactional table
Additional calendar attributes include:
- Year
- Month
- Month Number
- Quarter
- Year-Month
- Month-Year
The Month field was sorted using Month Number to preserve chronological order.
Several measures were created to support KPI monitoring and analytical calculations.
Total Sales =
SUM(financials[Sales])
Total Profit =
SUM(financials[Profit])
Total Units Sold =
SUM(financials[Units Sold])
Profit Margin =
DIVIDE(
[Total Profit],
[Total Sales],
0
)
Average Selling Price =
DIVIDE(
[Total Sales],
[Total Units Sold],
0
)
Total Discounts =
SUM(financials[Discounts])
The model also includes time-intelligence measures such as:
Sales Previous Year =
CALCULATE(
[Total Sales],
SAMEPERIODLASTYEAR(DateTable[Date])
)
Sales YoY Growth % =
DIVIDE(
[Total Sales] - [Sales Previous Year],
[Sales Previous Year],
0
)
Sales YTD =
TOTALYTD(
[Total Sales],
DateTable[Date]
)
Equivalent previous-year and growth measures were also created for profit.
YoY calculations remain available in the semantic model for analytical purposes, but they are intentionally excluded from the main dashboard KPIs because the source dataset contains only a partial 2013 period.
The Executive Overview provides a high-level view of company performance.
- Total Sales
- Total Profit
- Total Units Sold
- Profit Margin
- Sales by Country
- Sales by Product
- Monthly Sales Trend
- Dynamic Key Insights
- Year and Month filters
For 2014, the dashboard shows approximately $92M in sales, $13M in profit, 861K units sold, and a 14.1% profit margin.
The United States leads geographic sales with approximately $19.9M, while Paseo is the highest-selling product with approximately $27.1M in revenue.
October records the highest monthly sales performance in 2014 at approximately $12.4M.
The Product Analysis page focuses on product performance, profitability, and discount efficiency.
- Total Sales
- Total Profit
- Average Selling Price
- Profit Margin
- Sales by Product
- Profit by Product
- Profit Margin by Product
- Discounts vs Profit Margin
- Dynamic Product Insights
- Paseo is the strongest product by both sales and total profit.
- Montana achieves the highest product profit margin in the 2014 view at approximately 14.5%.
- Paseo receives the largest amount of discounts at approximately $2.1M while maintaining a profit margin of approximately 13.6%.
- The discount-versus-margin analysis helps identify whether higher discount exposure is associated with stronger or weaker product profitability.
This page evaluates geographic profitability and customer segment performance.
- Total Sales
- Total Profit
- Total Units Sold
- Profit Margin
- Profit by Country
- Sales by Segment
- Profit Margin by Segment
- Dynamic Market & Segment Insights
- France leads country profitability in 2014 with approximately $3.0M in profit.
- The Government segment generates the highest sales, with approximately $39.4M in revenue.
- Channel Partners achieves the highest segment profit margin at approximately 73.2%.
- The Enterprise segment records a negative profit margin of approximately -2.7%, highlighting a potential profitability issue despite its meaningful sales contribution.
The dashboard reveals several important patterns:
- Revenue is relatively diversified across the five geographic markets.
- Product performance is more concentrated, with Paseo significantly outperforming the rest of the portfolio in sales.
- High revenue does not necessarily imply the highest profit margin.
- Discount exposure varies substantially between products and should be evaluated together with profitability.
- Customer segments show major differences in margin performance.
- Enterprise generates substantial revenue but negative profitability, making it a clear candidate for deeper pricing and cost analysis.
- Channel Partners generates comparatively low revenue but exceptionally high margins.
- Monthly sales fluctuate throughout 2014, with particularly strong performance toward the end of the year.
These findings demonstrate why executive reporting should evaluate revenue, profit, margin, volume, discounts, and customer mix together rather than relying on sales alone.
The final report includes:
- Interactive Year and Month slicers
- Cross-filtering between visuals
- Dynamic KPI calculations
- Dynamic text-based business insights
- Dedicated Date table
- Time-intelligence measures
- Product ranking
- Geographic performance analysis
- Customer segment profitability analysis
- Discount vs profitability analysis
- Consistent multi-page dashboard design
- Page navigation sidebar
- Executive-oriented KPI cards
Project_04_PowerBI_Executive_Dashboard/
│
├── dashboard/
│ └── Executive_Dashboard.pbix
│
├── images/
│ ├── executive_overview.png
│ ├── product_analysis.png
│ └── market_segment_analysis.png
│
├── README.md
├── project_notes.md
└── .gitignore
This project demonstrates the complete development of a Business Intelligence dashboard, from dataset exploration and data modeling to DAX calculations, interactive visualization, business analysis, and executive reporting.
Rather than focusing only on visual design, the dashboard was built around business questions and decision-making.
The project demonstrates practical skills in:
- Power BI dashboard development
- DAX
- Data modeling
- Time intelligence
- KPI development
- Business analysis
- Data visualization
- Analytical storytelling
- Executive reporting
Martin Panelo
Data Analyst | Geophysicist | Scientific Computing
Analytical professional combining data analytics, scientific computing, and geoscience experience, with a focus on Python, SQL, Power BI, data visualization, and business-oriented problem solving.
- GitHub: PaneloMartin
- LinkedIn: Martin Panelo