gbazad93/AirFlow-ML-Data-Integration

An Airflow-based pipeline that fetches data from a free API, cleans and transforms it, and saves it to a database—ready for downstream machine learning.

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Experimental

This project helps data professionals automate the daily collection of weather data. It takes raw weather information from a public API, cleans and organizes it, and then stores it in a database. This prepared data is then ready for further analysis, like building predictive models or creating dashboards. Data engineers or analysts who need a reliable, automated way to feed external weather data into their systems for reporting or machine learning would find this useful.

No commits in the last 6 months.

Use this if you need to set up a robust, automated daily pipeline to fetch, clean, and store external weather data in a PostgreSQL database for downstream analytics or machine learning.

Not ideal if you are looking for a pre-built machine learning model or a dashboard, as this project focuses solely on the data integration pipeline.

data-integration weather-forecasting-data ETL-pipeline data-engineering predictive-analytics-data-prep
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 5 / 25

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Stars

16

Forks

1

Language

Python

License

Last pushed

Mar 26, 2025

Commits (30d)

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curl "https://pt-edge.onrender.com/api/v1/quality/data-engineering/gbazad93/AirFlow-ML-Data-Integration"

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