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UIDAI-Hackathon-2026-Analysis

A data-driven analysis and predictive model for Aadhaar lifecycle data.

📌 Project Overview

This project focuses on a data-driven approach to optimize Aadhaar services across India. By analyzing 1 million+ rows of lifecycle data (Jan-Dec 2025), I have developed a predictive model to forecast 2026 demand and identify infrastructure gaps.

🛠 Key Technical Methodology

Data Integration: Successfully merged 12 specialized UIDAI datasets into a single unified master engine using Pandas.

Advanced Cleaning: Standardized 55+ state name variations into 36 unique legal entities and implemented integrity checks to ensure 100% data validity.

Predictive Modeling: Built a forecasting engine using Linear Regression to predict a steady shift from new enrolments to biometric updates in 2026.

📂 Project Deliverables

👤 Author

Kidwai Moniza Javed

Theme: Data-Driven Governance & Predictive Modeling