Are you an LLM? Read llms.txt for a summary of the docs, or llms-full.txt for the full context.
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Quickstart

This is the shortest path from an empty workspace to a forecast you can reason about. Each step links to a detailed guide.

Connect a data source

Bring your historical data in by connecting a Source — a CSV/Excel file, a Databricks share, or a Snowflake table or view. Your raw values arrive as Measures.

Define what you track

Open Targets to see your Measures and to build Metrics — derived values calculated from a formula. Together, measures and metrics are the things you forecast.

Run a baseline forecast

Create a Forecast Version and run it. Galdera produces a baseline forecast from your history — no assumptions applied yet.

Layer on your assumptions

Add an Overlay to encode business judgment — "revenue grows 15% in Q3" — using a Scale, Override, or Offset operation.

Compare scenarios

Tag your overlay blocks with Scenarios and compare the outcomes against the shared baseline to see how different assumptions change the picture.