Ahmed Ali

AI & Data Science Practitioner • Microsoft Certified: Azure Data Scientist & Administrator • Power BI Data Analyst & Trainer

Project Overview 📊

Chicago Traffic Tracker is a data analytics project aimed at uncovering semi-real-time congestion trends in the city of Chicago. By leveraging traffic sensor data provided by the Chicago Department of Transportation, we extracted insights that can support transportation planning, mobility improvements, and smarter city infrastructure. The objective is to classify and analyze congestion levels using segment-based speed data from bus-mounted traffic sensors.

Dataset 🗂️

The project utilizes the Chicago Traffic Tracker – Congestion Estimates by Segments dataset. Key features include:

  • Over 1,000 segments with real-time updates every 10 minutes
  • Congestion estimates as a percentage of free-flow speed
  • Average speed, 85th percentile speed, and vehicle count
  • Timestamped data with geo-located segments (lat/long)

The data is publicly available via Chicago’s Open Data Portal in formats such as CSV, JSON, XML, and through an OData feed.

Tools & Workflow 🛠

We used Microsoft Power BI for data ingestion, transformation, and interactive visualization:

  • Data Ingestion: OData feed connected directly to Power BI
  • Transformation: Power Query for filtering, reshaping, and cleaning
  • Visualization: Custom route map visual to display congestion by segment

Chicago Traffic Tracker - Workflow

Live Demo 🔗

You can interact with the live dashboard below:

Acknowledgement ✅

This project is a part of ATS’s projects catalog, and has been developed in collaboration with my colleague, Abdur Rehman.