A business intelligence dashboard built specifically for Small and Medium Enterprises (SMEs) in Malawi to visualize sales trends, customer behaviors, and key performance metrics — enabling data-driven decisions and business growth.
# SME BI Dashboard (Malawi)
A professional, interactive Business Intelligence dashboard for Small and Medium Enterprises (SMEs) in Malawi. Built with Python, Streamlit, and Plotly, this dashboard empowers SME owners and analysts to visualize trends, monitor KPIs, and gain actionable insights from their sales and customer data.
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## 🚀 Features
- **Data Upload & Download**
Upload your own CSV data and download filtered/analyzed data as CSV or Excel.
- **Interactive Filtering**
Sidebar filters for Region, Product, and Date Range.
- **Key Performance Indicators**
Instant KPIs for sales, profit, and customer metrics.
- **Regional & Demographic Analysis**
Visualize sales by region, customer age distribution, and gender breakdown.
- **Product Analysis**
Sales and profit by product, with top/bottom product highlights.
- **Time Series Analysis**
Line chart for sales/profit over time with daily, weekly, or monthly aggregation.
- **Customer Retention & Churn**
See new vs. repeat customers and simple churn analysis.
- **Anomaly Detection**
Detect and visualize unusual sales patterns using an Isolation Forest model.
- **Sales Forecasting**
Predict future sales trends using Facebook Prophet with upper/lower bounds.
- **Customer Segmentation**
Visualize customer segments using K-means clustering.
- **Export Reports**
Download filtered data as Excel or CSV.
- **Modern, Responsive UI**
Clean, professional UI optimized for desktop and mobile.
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## 📊 Overview
SMEs in Malawi—whether a shop in Blantyre or a farm input dealer in Lilongwe—often lack access to robust analytical tools. This dashboard solves that with:
- Aggregated sales and customer data
- Automated business insights in plain English
- Interactive visualizations and smart diagnostics
- Low technical overhead with open-source tools
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## 📂 Project Structure
bi-dashboard-sme/
│
├── data/
│ └── sample_sales_data.csv # Sample dataset
│
├── src/
│ ├── anomaly_detection.py # Isolation Forest logic
│ ├── …