Data Model / Product Data Model

In brief: The data model (Product Data Model) defines how product information is structured in PIM: which categories and classes exist, which attributes and values are used, how variants are structured and how products relate to one another. This is where the greatest effort in PIM implementation lies, not in the technology.

Components of a data model

• Structure: Categories for navigation and classifications for characteristics.
• Attributes: Characteristics with a data type, unit and permitted values.
• Levels: Product and variant, with rules for inheritance.
• Relationships: Accessories, spare parts, sets (relationships).
• Contexts: Languages, countries and channels with their own values.
• Rules: Mandatory fields and validation checks for each category and channel.

Why the data model matters

A good data model enables online shop filters, meets retailers’ format requirements and keeps data maintenance to a minimum. A poor one creates duplicates, empty fields and manual work, and is difficult to change once the data has been migrated. It should therefore be defined before system configuration and designed around the output, starting with the requirements of the most important channels.

The Data modelling entry explains how to approach this.

See also

• Data modelling
• Properties / Attributes
• Classifications
• Categorisation rules
• PIM implementation