Accelerate your analytics with pre-built Lightdash content. ⚡️
Lightdash is an open-source BI tool—learn more about it in our docs. 🔍
The templates in this repo extend the Content as Code functionality, making your journey from source data to insights even faster.
If you have content that could benefit the wider Lightdash community, please feel empowered to open a PR and share it here! 🙌 A few tips:
- Minimize extra transformations: Stick as close to source data as possible, since everyone’s data modeling can differ. 🔧
- If you must do some modeling, clearly document it so others can adapt it. 📝
- Build you dashboards and charts in the Lightdash UI, then use
lightdash download
to get a draft template, and finally generalise and simplify!
This repo is organized by data type or domain (e.g., bigquery-usage-tracking). Each folder contains specific instructions, but here’s the gist:
- Navigate to the relevant folder (e.g., BigQuery) and review the included charts/dashboards. 📂
- Copy the yml files into a
lightdash
folder in the root of your dbt project. 📑 - If needed, create new dbt models/yml files for the underlying data. BigQuery, for example, may require a model pointed at
information_schema.jobs
. Tip -lightdash generate
will save you time here! ✨ - Adjust the content yml references to point to your own tables. ⚙️
- Finally, run
lightdash upload --force
to immediately push your new content to Lightdash. 🚀
For more details on how to extend your dashboards, metrics, or charts through version control, check out the Content as Code docs. Happy templating! 🎉