📊 Sales Revenue Forecasting with Business Decision Insights

---

📚 Table of Contents

• Project Overview
• Business Question
• Application Flow
• Screenshots
• Tech Stack
• Project Structure
• Forecasting Logic
• Business Decision Insights
• Run Locally
• Resume Bullet

---

🔍 Project Overview

Sales Revenue Forecasting with Business Decision Insights is a recruiter-ready analytics application that allows users to upload their own sales data, process it into a database, and instantly generate revenue forecasts with actionable business insights.

The project focuses on decision impact, not complex black-box models.

---

🎯 Business Question

“How much revenue should we expect in the near future, and what business actions should we take?”

This project explicitly answers the so what behind forecasting.

---

🔄 Application Flow

1. Upload a sales CSV file
2. Preview raw data for validation
3. Click Process & Analyze Dataset
4. Data is stored in SQLite and aggregated using SQL
5. Forecast KPIs, trends, and decision insights are displayed

Users explicitly control processing, improving trust and usability.

---

🖼️ Screenshots

1️⃣ Dataset Upload & Preview

---

2️⃣ Forecast Summary (KPIs)

---

3️⃣ Revenue Trend – 7-Day View (Short-Term)

---

4️⃣ Revenue Trend – 30-Day View (Mid-Term)

---

5️⃣ Business Decision Insights

---

🧩 Tech Stack

Layer	Tools
Language	Python
Data Processing	Pandas
Database	SQLite
Analytics	SQL, Time-Series Trends
Visualization	Matplotlib
App Framework	Streamlit
UI Styling	CSS (Glassmorphism, Gradients)

---

📂 Project Structure

sales-revenue-forecasting-with-business-decision-insights/
│
├── app/
│   └── app.py
├── scripts/
│   ├── load_to_sqlite.py
│   ├── create_daily_revenue_table.py
│   ├── trend_analysis.py
│   └── forecasting.py
├── data/
│   └── sales.db
├── screenshots/
│   ├── upload_dataset.png
│   ├── forecast_kpis.png
│   ├── trend_7_days.png
│   ├── trend_30_days.png
│   └── business_insights.png
└── README.md

---

🔮 Forecasting Logic

• Uses recent 30-day average daily revenue as baseline
• Generates:
  • Expected revenue
  • Best-case scenario (+15%)
  • Worst-case scenario (−15%)

The emphasis is on clarity and business interpretability.

---

🧠 Business Decision Insights

🔹 7-Day (Operational)

• Inventory readiness
• Staff scheduling
• Tactical promotions

🔹 30-Day (Planning)

• Replenishment cycles
• Marketing budget scaling
• Capacity preparation

---

▶️ Run Locally

python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate
pip install -r requirements.txt
streamlit run app/app.py

---