🚀 Production Ready 🐍 Python 3.10+ 🐬 MySQL 8.0 📊 Streamlit Framework
An end-to-end Business Intelligence (BI) & Data Engineering ecosystem designed for an artisan candle business. This project demonstrates advanced data manipulation skills, ranging from relational database architecture (3NF) and enterprise security to predictive modeling and automated reporting.
- Enterprise Security & Authentication: Integrated login system that validates users against encrypted credentials stored directly within the SQL database.
- Interactive Dashboard (Streamlit): Structured into 4 specialized corporate modules for seamless executive navigation.
- Advanced Business Analytics: Complex data visualizations (Area Charts, Scatter Plots, Donut Charts) mapping profit-to-volume correlations and KPIs.
- Predictive Forecasting: Machine Learning module predicting next-quarter revenue and demand based on historical seasonal trends.
- Automated Executive Reporting: One-click functionality to generate, format, and download deep-dive data reports in Excel (
.xlsx) format. - Optimized SQL Architecture (3NF): High-performance relational database schema ensuring full traceability of raw materials, suppliers, inventory, and sales.
database/- Production SQL schemas, user access tables, and transactional test data.python/app.py- Main user interface and layout execution of the BI Dashboard.python/analysis.py- Core analytics engine, security logic, and predictive forecasting algorithms.screenshots/- Visual assets and UI/UX documentation..gitignore- Version control exclusion file for environment security.
- Database Engine: MySQL
- Core Language: Python 3.x
- Data Science & Manipulation: Pandas, NumPy
- Data Visualization: Plotly Express
- BI Deployment Framework: Streamlit
- Automated Reporting: XlsxWriter
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Clone the repository:
git clone https://github.com/Codedchic25/LightInfinityCandles.git
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Install project dependencies:
pip install -r python/requirements.txt
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Launch the BI Dashboard:
cd python streamlit run app.py -
Demo Credentials:
- Administrator: User:
admin| Password:candle2024 - Standard User: User:
gabriela| Password:proiect2024
- Administrator: User:
The Forecasting Module leverages historical sales data time-series to project future revenue streams. By converting historical patterns into predictive insights, this engine directly assists stakeholders in:
- Optimizing raw material procurement.
- Eliminating supply-chain bottlenecks.
- Streamlining production schedules based on data-driven demand.
This platform is evolving into an AI-driven autonomous data assistant through the following roadmap:
- Conversational Analytics (LLM): Integration of LangChain and OpenAI API to enable non-technical stakeholders to query the MySQL database using standard natural language prompts.
- Automated AI Insights: Generating automatic, context-aware text summaries at the end of each fiscal cycle (e.g., "Sales increased by 10% due to Easter seasonal demand").
- ETL Pipeline Automation: Deploying a fully automated data pipeline via GitHub Actions to sync production database updates with the active dashboard daily.
Cojocaru Maria Gabriela
Data Analyst & SQL Developer Portfolio
Feel free to connect on LinkedIn or explore the code!