Waylaytics

Key Highlights

• Designed scalable data models for U.S. Census datasets
• Built interactive D3 visualizations for state and city comparisons
• Optimized MongoDB aggregation pipelines for performance

Architecture and Data

• Ingested and normalized U.S. Census and public datasets using Python
• Designed MongoDB schemas optimized for geographic queries
• Built aggregation pipelines to support fast comparisons across states and cities
• Exposed data through a Next.js backend consumed by D3 visualizations

Problem and Solution

Problem

Choosing where to live often requires comparing dozens of disconnected data sources — taxes, housing, crime, education, healthcare, and cost of living — making it difficult to make informed decisions.

Solution

Waylaytics aggregates public datasets into a unified platform, allowing users to compare U.S. locations through interactive visualizations and data-driven insights.

What's next for this project

• Incorporate additional datasets such as climate and employment statistics
• Enhance visualizations with predictive analytics and trend analysis
• Implement user accounts for saving favorite locations and custom comparisons