Internet Usage
Tracker & Analytics

Project Overview

A Python desktop application for enterprise internet usage monitoring — tracking which departments consume the most bandwidth, identifying peak usage hours, flagging non-productive browsing, and generating executive summary reports.

The tool reads usage logs, processes them with Pandas, and renders interactive visualisation charts via Matplotlib — all within a clean Tkinter GUI.

Core Analytics Modules

• Department Usage Analysis — bandwidth consumption by department and team
• Peak Hours Detection — hourly usage patterns to identify bottlenecks
• Daily Usage Trends — daily and weekly usage trend lines
• Top 10 Sites — most visited domains ranked by time and data usage
• Category Breakdown — productive vs non-productive category classification
• Productivity Scoring — department-level productivity score calculation
• Executive Dashboard — full summary report exportable as PNG/CSV

Technical Implementation

• Custom Tkinter GUI with tabbed navigation for each analytics view
• Pandas for data ingestion, cleaning, and aggregation pipelines
• Matplotlib embedded within Tkinter for live chart rendering
• CSV export for all aggregated reports — compatible with Excel/BI tools
• Logging system for audit trail — saves daily analytics logs
• Configurable thresholds for productivity classification

Use Case & Impact

Gives IT and management complete visibility into internet consumption without expensive enterprise tools. The productivity score helps identify departments with high non-productive browsing — enabling focused policy interventions.