
During two months on the Prof-Drake-UMD/INST767-Sp25 repository, J. Lewis established foundational project scaffolding and delivered a disaster data pipeline infrastructure. Lewis began by creating reproducible Python scripts and a detailed README to streamline onboarding and environment validation. The technical approach included integrating APIs for IMDb, OpenWeatherMap, and Ambee, and enriching disaster datasets with OpenStreetMap geocoding. Using Python and SQL, Lewis designed database schemas and implemented data ingestion, processing, and analysis pipelines. The work emphasized maintainability by documenting processes and refactoring legacy scripts, resulting in a clean, extensible codebase that supports repeatable analytics and efficient future development.

Monthly work summary for 2025-05 focusing on the Prof-Drake-UMD/INST767-Sp25 repository. Highlights include delivery of a disaster data pipeline infrastructure, geolocation enrichment, documentation scaffolding, and cleanup/refactor of legacy scripts. Emphasis on business value, maintainability, and technical skill demonstration.
Monthly work summary for 2025-05 focusing on the Prof-Drake-UMD/INST767-Sp25 repository. Highlights include delivery of a disaster data pipeline infrastructure, geolocation enrichment, documentation scaffolding, and cleanup/refactor of legacy scripts. Emphasis on business value, maintainability, and technical skill demonstration.
For 2025-04, delivered foundational scaffolding and data collection groundwork for Prof-Drake-UMD/INST767-Sp25. Implemented a test Python script to validate environment setup and published an initial README outlining project goals and early data collection scripts for IMDb and OpenWeatherMap. This groundwork creates a reproducible baseline to accelerate upcoming feature development and data pipelines, and improves onboarding for new contributors.
For 2025-04, delivered foundational scaffolding and data collection groundwork for Prof-Drake-UMD/INST767-Sp25. Implemented a test Python script to validate environment setup and published an initial README outlining project goals and early data collection scripts for IMDb and OpenWeatherMap. This groundwork creates a reproducible baseline to accelerate upcoming feature development and data pipelines, and improves onboarding for new contributors.
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