Project Overview

For Eyanu Catering, I developed a comprehensive analytics solution aimed at transforming their operational data into actionable business intelligence. The project’s goal was to provide management with clear, data-driven insights into sales performance, customer behavior, costing, and operational efficiency — helping guide strategic decisions from pricing to marketing and logistics.

Objective & Business Questions

The project was driven by key questions critical to Eyanu Catering’s growth:

Which services (menu items, catering packages, events) generate the highest revenue and profit margins?

What are the customer ordering and engagement patterns (frequency, peak times, order sizes)?

Where are cost-efficiencies and waste occurring (ingredients, delivery, labor)?

Which marketing channels or referral sources produce the most repeat customers?

How can performance be tracked over time (monthly/quarterly trends) to inform future planning and growth?

Technical Approach & Workflow

To address these questions and build a robust analytics pipeline:

Data Aggregation & Cleaning: I integrated multiple data sources — orders, menu items, costs, customer data — consolidating them into a unified schema while handling missing values, inconsistent formats, and duplicates.

Data Modeling: I designed relational tables for orders, customers, services, costs, and revenue streams to support flexible querying and reporting.

Dashboard Development: Leveraged a BI tool (e.g. Power BI / Tableau — whichever you used) to build dynamic interactive dashboards. Dashboards include revenue by service, profit margin analysis, customer segmentation, order frequency, cost vs profit heatmaps, and time-series performance charts.

Business Logic & Metrics: Created custom measures for KPIs such as gross margin, customer lifetime value, average order value, repeat customer rate, cost per event, and revenue growth rate.

Insight Generation: Through visualizations, identified trends in best-selling offerings, peak demand periods, high-cost items, and customer segments with growth potential.

Key Insights & Findings

From the analysis and dashboard, several actionable insights emerged:

Certain menu items and catering packages consistently delivered the highest profit margins while maintaining strong demand — ideal for promotional focus.

Orders peaked during specific weekdays and event types, allowing for optimized staffing and ingredient procurement to reduce waste and costs.

A subset of customers repeatedly ordered high-margin packages, suggesting the value of loyalty and referral programs.

Cost analysis revealed inefficiencies in certain service delivery workflows — presenting opportunities to streamline logistics and negotiate better supplier pricing.

Marketing and referral origin data highlighted channels that produced the most repeat clients, helping steer marketing spend more effectively.

Business Impact

The dashboard and insights deliver tangible business value to Eyanu Catering by:

Enabling data-driven pricing, menu selection, and service prioritization to maximize profit.

Informing staffing and supply planning to minimize waste and lower overhead costs.

Highlighting high-value customer segments to target with retention or referral incentives.

Supporting strategic decisions on marketing investment by showing which channels yield real returns.

Empowering management to track performance over time and respond proactively to seasonal or demand shifts.

Repository & Delivery

The full project — including dataset schemas, cleaned data extracts, dashboard files, and documentation — is maintained in a dedicated repository on GitHub. You are welcome to review the code, model design, and dashboard logic to see how insights were derived and structured for scalability and reuse.

Repository link: https://github.com/iyanusol/SQL-Project-Analysis
(or specify if there’s a dedicated “Eyanu Catering” folder / repo)