100K+ Doctor Data Project
Data Engineering & Lead Generation
A scalable data pipeline built to extract, clean, organize, and structure a large healthcare dataset into a usable business resource.
The Problem
The client needed a large dataset of US doctors but did not have a dependable way to collect, structure, and validate that information at scale. The data had to be usable, searchable, and organized for business use.
What the Business Needed
Data extraction
Web scraping
Data cleaning
Lead database
Validation
Large-scale structuring
What We Built
We built a scalable data extraction and cleanup pipeline designed to gather and organize a 100,000+ record business dataset into a usable, reviewable structure.
Extraction pipeline
Automated collection of structured data from web sources.
Automated cleanup
Normalization and validation to reduce unusable or inconsistent records.
Business dataset
Organized data made ready for marketing, outreach, or internal analysis.
Large-volume processing
Built to handle scale without sacrificing data quality.
Technical Stack
Python · Scraping automation · Data cleaning · Structured dataset pipeline
Result
Built a structured, large-scale dataset that was organized and usable for decision-making rather than scattered across raw source content.