Used a synthetic retail dataset to forecast 30-day sales across product categories like Clothing, Electronics, and Beauty. Grouped historical sales data and developed category-specific time series models using Facebook Prophet. Forecasts were exported and integrated into a Power BI dashboard for business users, enabling comparison of predicted vs actual sales and highlighting seasonal trends and anomalies.
Key features included a forecast vs actual line chart, KPI cards, peak sales day insights, and accuracy metrics. While Prophet smoothed over some promotional spikes, the project demonstrated how to apply machine learning outputs in business intelligence environments.
Tools & Skills: Python, Prophet, Pandas, Matplotlib, Power BI, Google Colab, GitHub, Time Series Forecasting, Data Visualization, Dashboard Design
Built a full-stack event management web application that allowed clients to book specialized planners for events like birthdays, engagements, and anniversaries. The system handled client registration, event scheduling, and planner assignment through a responsive PHP interface backed by a SQL Server database.
Clients could submit event details and receive planner matches based on availability and event type. Bookings were displayed on an interactive calendar using FullCalendar.js, and admins could manage records through modals and in-page updates. The project was deployed to Azure App Service with continuous integration via GitHub Actions.
Tools & Skills: PHP, SQL Server, Bootstrap, FullCalendar.js, GitHub Actions, Azure, Web App Deployment, CRUD Development, Calendar Integration
Designed and developed a lightweight mobile app to help users track meals and monitor daily calorie goals with ease. Built using React Native and Expo, the app features a clean dark/light theme toggle, meal logging with calorie input, and automatic calculation of total and remaining calories. All interactions are kept on a single screen for speed and simplicity. The visual identity emphasizes minimalist UI design and a monospaced Courier font for a modern-retro feel.
Key features include a custom calorie goal input, dynamic meal tracking, and a responsive interface across dark/light modes. Developed in VS Code and shared using Snack Expo for live previews and collaboration.
Tools & Skills: React Native, Expo, JavaScript, Snack Expo, VS Code, Hooks, Mobile UI/UX Design, State Management
Designed a dynamic Power BI dashboard that visualized sales performance across product categories, regions, and time periods using a synthetic retail dataset. The dashboard included interactive filtering by product line, store location, and sales rep, enabling clear insight into revenue trends, seasonal patterns, and top-performing products. Implemented custom DAX measures to calculate year-over-year growth, profit margins, and customer retention. The final solution enabled stakeholders to identify underperforming regions and optimize inventory decisions based on data-driven insights.
At Baig Enterprises, analyzed over 10,000 sales transactions, improving inventory accuracy by 15%. Reduced query response time by 30% through optimized stored procedures and indexing. Contributed to SAP ERP customization for pharmaceutical logistics, enhancing system functionality and integration.
Developed a Power Apps application that reduced syllabus search time by 70%. The tool used an AI model to extract structured data from 100+ PDF syllabi and stored it in a SQL database. A built-in professor search feature scraped RateMyProfessor reviews, enabling fast lookup across 3000+ instructors and courses.
Created a complete relational database system for a fictional company. Designed ERDs in LucidChart, normalized schemas, and wrote advanced SQL queries in SSMS. Delivered a robust, efficient system tailored to key business processes, enabling structured reporting and scalability.
Built a Python-based app using the Spotify API to deliver personalized playlist recommendations. The system processed and categorized 50,000+ songs using audio features such as mood, genre, and energy levels. Collected user input to match songs dynamically, with 90%+ satisfaction in informal tests. Ensured efficient API interaction and secure authentication.
Built a multi-dashboard Tableau project visualizing Spotify data trends across metrics like popularity, danceability, and energy. Enabled dynamic filtering and comparison of song attributes, providing insights into listener preferences and music trends over time.