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Built an Excel reporting dashboard that transforms order-level data into actionable sales metrics. The workbook calculates revenue, order counts, average order value, and monthly performance, with formula-driven summaries and visualizations that update as the underlying data changes.
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One business problem. Three analytical routes. One data-driven story. ☕📊
I turned raw business data into actionable decisions—not just another Power BI dashboard.
For the Onyx Data October 2026 Challenge, I worked on the Sunrise Coffee Chain analytics project, analyzing store performance, profitability, customer loyalty, revenue mix, and trading patterns across 60 UK stores (2023–2024).
🔹 My Analytical Approach
1️⃣ Python — Data Preparation
Cleaned and prepared the source datasets to establish a reliable foundation for analysis.
2️⃣ SQL — Business Analysis
Investigated store-level profitability, cost pressure, customer loyalty, revenue contribution, and trading patterns.
3️⃣ Power BI — Interactive Dashboards
Built a 3-page interactive report featuring advanced DAX measures, KPI cards, YoY comparisons, profitability analysis, and business-focused visualizations.
📊 Key Findings
• £89.7M Revenue | £16.9M Net Profit
The business recorded an aggregate net profit margin of 18.8% across the analysis period.
• Store Location Matters
Transport-Hub stores achieved a 25.1% aggregate net profit margin, compared with 18.6% for High-Street stores.
• An Area Requiring Attention
South London Corner recorded a £50.5K net loss over 24 months.
• Product Revenue Contribution
Espresso contributed 45.7% of daily revenue, while food contributed 26.1%.
• Trading Patterns
Average daily revenue was approximately 24% lower on weekends and 33% lower on UK bank holidays than on regular trading days.
💡 My Biggest Takeaway
Revenue alone does not tell the whole story. Understanding profitability, cost pressure, product contribution, and trading patterns helps businesses identify where to improve performance and make better decisions.
🔗 Explore the Complete Project
GitHub: https://github.com/SajeebTheAnalyst/sunrise-coffee-chain-analytics
If you were advising the management team, which finding would you investigate first—and why?
#DataAnalytics #SQL #PowerBI #Python #DAX #BusinessIntelligence #DataVisualization #OnyxData
I would investigate South London Corner first. Break the 24-month loss into store-month revenue, direct costs and allocated costs, then compare it with similar stores over matched trading periods. Reconcile at store-month grain before joining product or loyalty tables so a...
Mobile Dashboard UI Exploration
A clean and modern analytics dashboard designed to make data easier to understand at a glance.
This exploration focuses on minimal UI, intuitive navigation, clear data visualization, and a balanced layout that brings key business insights to the forefront.
✨ Minimal aesthetics
📊 Interactive analytics & data visualization
💜 Clean typography with vibrant accents
📱 A seamless mobile-first experience
Good design isn’t just about how data looks — it’s about how effortlessly people understand it.
What do you think of this dashboard concept?
#UIDesign #UXDesign #MobileAppDesign #DashboardUI #DataVisualization #Figma #ProductDesign
Workbook with synthetic order rows across January–June 2026. The overview calculates revenue ($6,707), order count (85), average order value ($78.91), and monthly totals and order volumes using Excel formulas. The revenue chart is linked to those calculations.
