Creating Models from Table
Creating a model from a table is a quick way to generate a semantic layer model with auto-detected dimensions and measures. Wobby analyzes your table structure and sample data to classify columns automatically.
When to Use This Method
Use "From Table" when you want:
Quick model generation from an existing table
Auto-detected columns classified as dimensions or measures
A starting point that you can refine manually
Speed over customization - get a working model fast
How to Create a Model from Table
Navigate to Models in the left sidebar
Click Create Model
Select From Table
Choose a data source from the dropdown
Search or browse to find your table
Click on the table to start generation
Table Selection
The table list shows:
Table name with schema path (e.g.,
public.orders)Existing model count - badge showing if models already exist for this table
Use the search box to filter tables by name.
Generation Process
After selecting a table, Wobby:
Analyzes columns - Reads column names, types, and sample data
Classifies columns - Determines which are dimensions vs measures
Generates expressions - Creates appropriate SQL expressions
Sets the grain - Identifies the primary key or unique identifier
Detects relationships - Finds foreign key connections
What Gets Generated
Dimensions are created for columns that represent:
Dates and timestamps
Categories and enums
IDs and foreign keys
Text attributes
Measures are created for columns that represent:
Numeric values suitable for aggregation
Counts and quantities
Relationships are detected based on:
Column naming patterns (e.g.,
customer_id→customers)Foreign key constraints
Tips
Review auto-generated items - The AI does its best but may misclassify some columns
Add descriptions - Help agents understand what each dimension/measure represents
Set up filters - Add common filters like "active only" or "last 90 days"
Check relationships - Verify detected relationships are correct
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