coffee-analytics
Data analytics project for personal coffee ratings – tracks, transforms, and visualizes coffee preferences
This is a full-stack data analytics project designed to track and analyze personal coffee ratings. It captures coffee data from a mobile app, processes it through a dbt project, and visualizes insights using an Evidence report. The pipeline automates data export to S3, transforms it in MotherDuck, and deploys the interactive report on Vercel.
- Tracks coffee ratings via iOS/macOS database app
- Automates data export to S3 in CSV format
- Transforms raw data using dbt in MotherDuck
- Generates interactive data reports with Evidence
README
View on GitHub ↗The combined dbt/Evidence project for Sean's coffee ratings log.
The Full Stack
- Data is tracked in Collections, a macOS/iOS database app with Shortcuts support.[^airtable]
- A shortcut exports the data to CSV, converts column names from
Title Casetosnake_case, and saves the files to S3 via S3 Files. This shortcut is run on a schedule with automations. - This dbt project transforms the data in MotherDuck.
- The Evidence site is deployed on Vercel.
[^airtable]: Until recently, this was done in Airtable and synced via Fivetran.
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