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afodunrinbikunmi-data/superstore-sales-analysis

Domain:

socioeconomic
Creator:
afo
Host:
End-to-end Power BI analysis of a $12.6M retail dataset. Uncovered that 52% of orders were unprofitable due to undisciplined discounting and identified $136K+ in losses across Africa/EMEA markets. Includes DAX modeling and strategic recovery plans ## Global Superstore Sales Analysis: Identifying Revenue Leakage and Market Inefficiency Revenue is vanity, profit is sanity. This project uncovers how a global retailer managed to generate $12.6M in sales while over half of its transactions were actually losing money. Uncovered that 52% of orders were unprofitable due to undisciplined discounting and identified $136K+ in losses across Africa/EMEA markets. ## Project Summary A comprehensive sales performance analysis of a global superstore covering 51,290 orders across 7 markets, 3 product categories, and 4 years (2011–2014). The goal was to identify what drives revenue and profitability and where the business is losing money despite strong sales growth. ## Dataset Overview | Table | Rows | Description | |---|---|---| | **Orders** | 51,290 | Primary fact table — all transactional data | | **Returns** | 1,174 | Returned order records | | **People** | 15 | Regional manager assignments | **Period:** January 2011 — December 2014 **Coverage:** Global — all major markets and continents ## Key Columns in the Dataset | Column | Description | |---|---| | **order_id** | Unique order identifier | | **order_date / ship_date** | Order and shipment dates | | **customer_name / segment** | Customer details | | **category / sub_category** | Product classification | | **sales / profit / discount** | Core financial metrics | | **market / region / country** | Geographic hierarchy | | **ship_mode / shipping_cost** | Logistics data | ## Tools Used | Tool | Purpose | |---|---| | **Microsoft Excel** | Data profiling, cleaning, calculated columns, PivotTable analysis | | **Microsoft Power BI** | Data modelling, DAX measures, interactive dashboard | | **Power Query** | Table relationships and data transformation | | **DAX** | Custom KPI measures and time intelligence | ## Data Cleaning & Preparation - Confirmed 51,290 rows and 21 columns with no missing values - Verified and corrected date and numeric column formats - Identified 3-tabl …