Web Traffic Analyzer — Data-Driven Behavior Insights
A data-driven application that analyzes user behavior and traffic trends to generate insights — the full data science workflow from raw logs to visual answers.
⚠ The Challenge
Raw traffic data is noisy and unreadable: timestamps, paths, and user agents in bulk. The value is in the questions it can answer — what do users actually do, where do they drop off, what's trending — and getting there requires a disciplined pipeline, not a one-off notebook.
⚙ The Approach
I built the analyzer in Python using the end-to-end workflow I document in my writing: data cleaning and validation, exploratory analysis with Pandas, feature derivation (sessions, trends, segments), and clear visual reporting so non-technical stakeholders can read the results.
✓ The Outcome
A reusable analysis application that turns raw traffic data into behavior insights and trend reports — a template for the analytics and data-processing work I build into client dashboards and automations.