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Breathe Pipeline

The why

This project hits a couple of big themes for me. I was seeking out applications to practice BI and data engineering tools when Claude noted the connection with the Breathe app I deployed a few weeks ago. I have been collecting real data from that app and have been wanting some insights—especially after a recent flare-up that required an unusually large amount of inhaler usage. My hope is that I can inspire some exciting tool use and practice my skills with this deeply personal application.

The architecture

Breathe app —> Google Sheets —> Python script extraction —> DuckDB —> dbt —> Evidence —> Netlify

  • Breathe app: mobile app to collect symptom tracking and inhaler usage.
  • Google Sheets: operational database to capture event records.
  • Python script extraction: chosen as a simpler alternative than Airbyte for deployment.
  • DuckDB: powerful analytics database that runs locally.
  • dbt: transformational and semantic data layer.
  • Evidence: clean and simple visualization tool that plugs into SQL databases and deploys as a static file.
  • Netlify: hosting site which can be easily triggered from GitHub actions.

Stack

Tools and versions once I know them.

How to run

Once it’s operational…

Current status

Where is the project… update after each session.

Transformation working with DBT project. Analytics marts containing useful reporting data created.

Next action

Literally just the next step or concrete action to take. Not a backlog or roadmap… just the next step. Overwrite this each time I work on the project.

Check out Evidence and test out the visualization layer.

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