Build a dashboard from a semantic data layer
Use a coding agent with Graphene to define metrics, query your warehouse, and publish a report with charts and screenshots.
- What they did
- A team used Graphene, an npm CLI, inside a project or an existing repo such as dbt. They created semantic models in .gsql files and page content in markdown, then started the local server and asked a coding agent to answer a question, assemble a dashboard, or update the model. The agent generated GSQL queries and chart components while the CLI validated syntax, rendered the pages, and produced screenshots so the agent could keep refining the output.
- How it went
- The setup is described as a way to make analysis work about 10x faster and keep page styling consistent by default. It supports Snowflake, BigQuery, ClickHouse, Postgres, MotherDuck, and DuckDB. No measured results were provided, and using it without Graphene Cloud needs git plus a coding agent; commercial use also requires a separate agreement.
- Tips
- Good for teams that already keep data in a warehouse and want repeatable reports. Treat anything that would write, publish, or change data as a checkpoint and pause for approval first.
Try it yourself with Claude Code
I want to create a data analysis report for [business question] using [warehouse or local data source]. Set up a simple semantic layer for [key tables, metrics, joins] in this project, then build a dashboard or report with charts that answers the question. Use the files in this folder, show me the query behind each chart, and stop before any step that would publish, send, delete, or modify data so I can approve it first. If you need to change the model or layout, explain the change before applying it.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
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