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Introduction to Data Model Concepts

SKULaunch is built around a structured product data model. This section introduces the core concepts you will see throughout the platform and explains what each one is used for.

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Written by SKULaunch Support
Updated over 4 months ago

Taxonomy

A taxonomy is how products are organised into a logical hierarchy.

It defines where a product sits within your overall product structure and determines which families and attributes apply to it.

Taxonomy is used to:
• Organise products consistently
• Apply the correct family and attributes
• Support filtering, navigation, and downstream mapping

Family

A family is a template for a specific type of product.

All products in a family share:
• The same set of attributes
• The same validation rules
• The same enrichment logic

Families are where most product data work happens in SKULaunch.

Attribute

An attribute is a single piece of structured product data.

Examples include:
• Brand
• Material
• Length
• Power rating

Attributes have a defined type, optional validation rules, and may use units or lists of values.

Attributes are the foundation of consistent, high-quality product data.

Attribute Group

An attribute group is a way of organising attributes within a family.

Attribute groups:
• Improve the editing experience
• Make large schemas easier to understand
• Do not affect exports or validation

They exist to help people, not systems.

Input Attribute

An input attribute captures raw or source data.

This includes:
• Supplier product names
• Existing descriptions
• Codes and identifiers
• Unstructured content

Input attributes are often incomplete or inconsistent and are used as inputs for enrichment and AI processing.

Enriched Attribute

An enriched attribute holds cleaned, structured, and validated data.

These attributes:
• Follow strict formats
• Use standardised values
• Are ready for publishing

Enriched attributes are what flow into channels, PIMs, and marketplaces.

List of Values (LoV)

A List of Values is a controlled set of allowed values for an attribute.

LoVs are used to:
• Standardise data
• Prevent free-text variation
• Improve filtering and search

Examples include colours, materials, formats, or classifications.

Measurement

A measurement represents a measurable concept such as length, weight, or power.

Measurements:
• Define what is being measured
• Control which units are allowed
• Support consistent handling of numeric data

Measurements help keep dimensional data accurate and comparable.

Unit

A unit defines how a measurement is expressed.

Examples include:
• Millimetre
• Kilogram
• Watt

Units allow SKULaunch to normalise and validate numeric values correctly.

Channel

A channel represents where product data will be used or published.

Examples include:
• Ecommerce
• Marketplace
• Print
• Source data

Channels allow different rules, requirements, and completeness checks to be applied depending on the destination.

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