Project Monitoring

Client:

Government

Data Processing

2024

Software: MS Access, MS Excel
Database: Access, SQL Server
Programming: Python (Pandas, Sci-kit Learn, Beautiful Soup), VBA

Automate the collection and storage of Google Alerts for monitoring published articles online.

Enhance data quality through formatting, cleaning, and machine learning-based filtering.

Reduce manual review effort by filtering out irrelevant alerts based on historical data.

Provide daily automated email reports with the most relevant articles for stakeholders.

Implemented automated retrieval of Google Alerts based on predefined criteria.

Developed a SQL Server database to store and manage collected alerts.

Used Python (Beautiful Soup & Pandas) to clean and format data, ensuring consistency.

Applied machine learning (Scikit-Learn) to filter out irrelevant alerts based on past review patterns.

Designed an automated reporting system that compiles relevant alerts and sends daily email spreadsheets to stakeholders.

Reduces noise and manual effort by filtering out irrelevant alerts through machine learned classification.

Improves efficiency in monitoring published articles with daily automated reports.

Enhances decision-making by providing only the most useful and relevant articles.

Ensures structured storage and retrieval of related data for future retrieval.