Add Streamlit-Based AI Dataset Validator Tool with Real-Time File Upload and Anomaly Detection#101
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Stanley1414 wants to merge 3 commits intoRedback-Operations:mainfrom
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Add Streamlit-Based AI Dataset Validator Tool with Real-Time File Upload and Anomaly Detection#101Stanley1414 wants to merge 3 commits intoRedback-Operations:mainfrom
Stanley1414 wants to merge 3 commits intoRedback-Operations:mainfrom
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…al runs, total distance, avg speed, avg pace) added; saved cleaned data and stats.
Added requirement gathering document for Project 3, including team discussions, stakeholder inputs, and data specifications.
🔒 Security Scan Results✅ No critical security issues detected. The code has passed all critical security checks. |
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should be in a subdirectory, not the root of the repository. Closing PR |
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This pull request introduces a Streamlit-based AI Dataset Validator tool with the following core functionalities:
🔹 Real-Time File Upload Support
Users can upload datasets (CSV, Excel, JSON) via an intuitive web interface. The tool handles live data uploads for quick inspection and feedback.
🔹 Automatic Format Conversion
Uploaded files are automatically converted to a standardized structure suitable for processing and analysis.
🔹 Anomaly Detection & Correction
Built-in validation checks identify missing values, outliers, and inconsistent entries. Where possible, the tool provides automated suggestions or corrections.
🔹 ETL Pipeline Integration
The tool integrates with the existing data warehouse ETL pipeline to improve data quality at ingestion.
🔹 README and Documentation Updates
Project documentation updated to reflect usage instructions and architecture overview.
This tool significantly enhances the data preparation workflow for the Redback Data Warehouse project by empowering users to validate and sanitize datasets before ingestion.
Please review and advise on improvements or testing feedback.