my first line is never "love your work". it's one thing the owner can check on their own site in ten seconds, next to something good about them. what's the first line of yours right now?

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...