Concepts

Deep understanding of Datasculpt's domain model.

Why This Section

The Getting Started section shows you how to use Datasculpt. This section explains why it works the way it does.

Read this section when you want to: - Understand what structural metadata captures - Debug unexpected inference results - Extend Datasculpt for your domain - Integrate Datasculpt into a larger system

Concept Map

flowchart TD
    A[Structural Metadata] --> B[Shapes]
    A --> C[Roles]
    A --> D[Grain]
    B --> E[Evidence]
    C --> E
    D --> E
    E --> F[Decision Records]

Core Concepts

Concept	Question It Answers
Structural Metadata	What category of metadata is missing?
Evidence	What facts do we observe about columns?
Shapes	What structural pattern does the data follow?
Roles	What purpose does each column serve?
Grain	What uniquely identifies each row?
Decision Records	How do we trace inference decisions?

Reading Order

If you're reading cover-to-cover:

1. Structural Metadata — The problem Datasculpt solves
2. Evidence — The raw material for inference
3. Shapes — The first major inference
4. Roles — The second major inference
5. Grain — The third major inference
6. Decision Records — How everything is captured