Interactive Power BI dashboard analyzing $1.46 million USD in sales across 5,654 orders from a multi-category e-commerce business (2023 – 2025).
- Total Revenue: $1,456,309 | 5,654 orders
- Average Order Value: $1,456
- Top Category: Sports → $319K (21.9%)
- Top 3 Categories: Sports ($319K) → Electronics ($295K) → Clothing ($289K)
- Highest-Spending Segment: Customers 46+ years old
- Top 10 customers contribute >$47K in revenue
- Peak sales day: Friday | Preferred payment: Credit Card ($398K)
- Women outspend men in Sports | Men dominate Electronics
- Best month ever: March 2023 (~$78K)
- Performance Analysis: Products segmented into High/Low Performance based on sales vs category average
- Performance Metrics: High Performance Revenue vs Low Performance Revenue with distribution analysis
| Page | Focus Area | Visualization Type |
|---|---|---|
| 1 | Executive Summary | KPI Cards + Monthly Trend Line |
| 2 | Sales by Category & Geography | Horizontal Bars + Sunburst Chart |
| 3 | Customer Analysis | Age Groups + Top 10 Customers Table |
| 4 | Sales by Day & Payment Method | Line + Column + Detailed Matrix |
| 5 | Top 3 Categories Deep Dive | Large KPIs + Horizontal Bars |
| 6 | Sales by Category & Gender | 100% Stacked Columns + Custom Banners |
| 7 | Monthly Evolution 2023–2025 | Chronological Horizontal Bar |
| 8 | Top 5 Locations by Revenue | Clustered Bar Chart |
| 9 | Product Performance Analytics | Performance KPI Cards + Ranking Table + Donut Chart + Comparative Analysis |
Advanced Features
- Complex DAX measures (dynamic ranking, conditional segmentation, performance classification, dynamic titles & formatting)
- Simulated real-world ETL process extracting data from SQL Server and AWS Redshift-like structures using Power Query
- Interactive filters, drill-through, bookmarks, custom tooltips
- Professional design focused on executive-level data storytelling
- Performance analytics with product segmentation and ranking algorithms
- Product performance classification (High/Low) with category-based benchmarking
- Automated product ranking and revenue segmentation by performance tier
- Portfolio.pdf → Full dashboard export (9 pages)
DASHBOARD.pbix→ Interactive Power BI filesynthetic_ecommerce_data.csv→ Source synthetic dataset
- Power BI (Data Modeling, Advanced DAX, Dashboard Design)
- Power Query (simulated enterprise ETL pipelines)
- SQL Server & cloud data warehouse concepts (AWS Redshift)
- Excel Advanced
- Python for data processing and automation when required
- Unix environment experience
- Business-oriented data visualization & storytelling
- Performance analytics and product segmentation methodologies
- KPI development and comparative analysis frameworks
I'm actively open to Data Analyst, Business Intelligence Analyst, or BI & Analytics roles at data-driven companies.
Let's connect and discuss how I can help your team turn raw data into strategic advantages.
Contact
📧 Email: [email protected]
📱 Phone / WhatsApp: (+52) 55 6400-3686
💼 LinkedIn: https://www.linkedin.com/in/marcodata19
🐙 GitHub: https://github.com/MarcoData2
Based in Mexico City | Open to relocation abroad (relocation expenses covered) | Available for remote, hybrid or onsite roles worldwide