Project Details

This project is an intelligent, "self-aware" AI chatbot designed to serve as a dynamic portfolio, answering questions about my skills and projects by querying my GitHub profile in real-time.
It's built on an advanced Hybrid Retrieval-Augmented Generation (RAG) system that intelligently combines API calls, semantic search, and fuzzy matching to find the most accurate information.
A key feature is the end-to-end data analytics pipeline built to monitor the chatbot's performance and user engagement.
Data Capture: Every user interaction is logged in real-time to a Google Sheet, creating a live dataset.
Data Analysis & Visualization: A separate, decoupled Streamlit dashboard reads this data. Using Pandas for data manipulation and Plotly for visualization, it provides insights into popular questions, user engagement, and conversation patterns.
This project demonstrates a powerful combination of skills in AI & NLP, data analysis, and building data-driven applications.

Project Details

Developed an enterprise grade Power BI dashboard that transformed decision-making by providing a holistic, 360-degree view of business performance. The project successfully addressed a critical need for data driven insights following a period of financial uncertainty
This project showcases my proficiency in the full BI lifecycle:
ETL & Data Modeling: Integrated data from SQL and CSVs using Power Query. Architected a robust and scalable Galaxy Schema to manage complex business relationships
Advanced Analytics (DAX): Wrote over 30 complex measures to translate raw data into actionable KPIs, including Time Intelligence, dynamic P&L statements, and forecast accuracy calculations
Visualization & Self-Service BI: Designed five distinct report pages for Finance, Sales, Marketing, Supply Chain, and Executive teams. Implemented Field Parameters to empower non-technical users with flexible analysis
Outcome: Delivered a powerful tool that serves as the single source for strategic decisions

Live Interactive Dashboard

Project Details

This project showcases a complete data analytics journey, transforming raw user expenses into actionable financial insights. It demonstrates management of the full data lifecycle, from collection to interactive dashboarding.
The data pipeline begins with a Streamlit UI for data capture, with all transactions structured and stored in a MySQL database. A backend API serves this data on demand for analysis.
The core of the project lies in the analytics modules, where Pandas is used to:
Process raw data and create dynamic pivot tables for category-based spending analysis.
Calculate key performance indicators (KPIs) like total spend, average transaction value, and month-over-month percentage change.
These insights are delivered through a multi-tab interactive dashboard, providing a clear and compelling view of financial trends. This project highlights my skills in data processing, metric calculation, and building end-to-end analytical solutions.

Project Details

This project simulates a real-world scenario where I acted as a data analyst for AtliQ Hardware, a consumer goods company. Business stakeholders frequently required immediate, data-driven answers to specific questions but lacked the ability to query the database directly.
My role was to bridge this gap. I received 10 ad-hoc requests from various departments and was responsible for delivering timely and accurate data. I wrote efficient, readable SQL queries to extract the precise information needed for market analysis, product performance comparisons, and sales reporting.
Key Skills & Outcomes:
Problem Solving: Translated complex business questions into precise SQL logic.
SQL Proficiency: Authored 10 unique queries to retrieve targeted datasets.
Business Acumen: Provided data that empowered stakeholders to make informed, strategic decisions.
Documentation: Organized all queries, results, and insights into a well-structured GitHub repository for transparency and review.

Project Details

This project is a comprehensive business intelligence dashboard created entirely in Microsoft Excel to provide a multi-dimensional view of sales and financial performance. The goal was to build an intuitive and interactive tool for stakeholders to easily analyze key business metrics without needing specialized software. The dashboard comprises several interconnected analytical views:
P&L Analysis: A detailed breakdown of Net Sales, COGS, and Gross Margin % by country to assess profitability.
Performance vs Target: A year-over-year (YoY) analysis that uses conditional formatting to instantly highlight performance variances against set targets.
Quarterly & Divisional Summaries: Dynamic reports built with Pivot Tables to track seasonal trends and high-level divisional growth.
Product-Level Reporting: Granular analysis of sales by product line to identify top performers.
This project demonstrates proficiency in advanced Excel for data analytics, and creating interactive dashboards.