🔍 Eligibility Case Review Tracker

Python-based data validation tool designed to support QA and structured data review in high-volume operational environments. Built around rule-based checks to identify missing, invalid, or inconsistent data before downstream processing or reporting.

Processes CSV or Excel inputs and generates a clear output of data quality issues for review.

🔧 What It Does

• Loads structured data from CSV or Excel files
• Applies validation checks for missing, invalid, or inconsistent values such as dates, IDs, and key fields
• Flags records that require review based on defined rules
• Outputs results to error_report.csv for QA or audit follow-up

🧰 Tools Used

• Python (pandas)
• Microsoft Excel
• CSV and Excel structured data formats

📁 File Overview

• demo_data.csv - Sample dataset for testing
• data_checker.py - Validation and rule-checking script
• tracker_template.xlsx - Optional structured input template

▶ How to Use It

1. Populate demo_data.csv or use the Excel template
2. Run data_checker.py
3. Review error_report.csv for flagged issues

📌 Purpose

Built to reflect real-world data validation and QA workflows across regulated and high-volume environments. Focuses on improving data integrity, enforcing consistency, and reducing rework by identifying issues early in the process.