An interactive and intelligent Sales Dashboard built with Streamlit, powered by a custom AI agent, and designed for KPI reporting and data-driven decision-making.
This project helps sales teams and analysts visualize trends, revenue, and returns efficiently, with smart filters and a built-in assistant to answer business queries.
- 🎯 KPI Highlights: No. of Sales, Returns, Revenue, and Loss.
- 📈 Visual Insights: Line chart, Stacked Bar Graph, and Treemap to explore monthly and category-wise sales.
- 🤖 AI Assistant Manager: Ask questions about your data using a conversational interface (RAG-based agent).
- 🔎 Interactive Filters: Filter by year and product category for dynamic updates across all visualizations.
- 💡 ETL Optimization: Backend pipeline engineered with Azure Data Factory for high-volume data handling (1M+ rows).
- MongoDB (via
pymongo) - Python: Streamlit, Plotly, Pandas
- LangChain: RAG-based AI Agent
git clone https://github.com/munas-git/AI-powered-sales-dashboard.git
cd sales-dashboard-aipython -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
streamlit run app.py
The built-in assistant can answer business queries like:
- "What's the highest-selling category in 2024?"
- "Show total return losses for the last two years."
- "Which month had peak revenue?"
- "How many returns were recorded in Q1?"
- "What was the average revenue per category in 2023?"
- "Compare sales vs returns for Capsicum."