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A schema in cofi.ai defines the structure of a database — it determines how data is organized, labeled, and related within your workspace. Think of it as the blueprint that tells the system what each column means, what type of data it contains, and how it connects to other datasets.
Schemas ensure consistency, accuracy, and flexibility when transforming raw data into actionable insights.
A schema describes the design of your database, including:
Schemas allow cofi.ai to interpret and process data correctly — ensuring that metrics, dashboards, and models all speak the same “data language.”
Every column in your database is assigned a specific type that defines how the platform treats it.
| Column Type | Description | Example |
|---|---|---|
| Unmapped | Raw data that has not yet been categorized or processed. | “Temp_Column1” |
| Measure | Numeric values used for aggregation and metric calculations. | “Revenue,” “Headcount” |
| Dimension | Categorical data used for grouping, filtering, and drill-downs. | “Region,” “Department” |
| Formula | Custom-calculated fields derived from other columns. | “Profit = Revenue – Expense” |
| Date | Time-based information used for trends or time series analysis. | “Transaction Date,” “Hire Date” |
Schemas define how data connects across databases.