Metadata Layer
A metadata layer holds the definitions, types, rules and relationships that describe your data, so people and systems know what each field means and how to use it.
What is Metadata Layer?
A metadata layer is the part of a system that holds data about your data: the definitions, types, rules and relationships that tell people and software what each field means and how to use it. In a product catalog it describes attributes, units, allowed values, categories and how products relate. The metadata layer sits between raw records and the apps that use them. A product record says the weight is 2.5; the metadata layer says the field is called weight, is a number in kilograms, is required for shipping and appears in filters. It differs from a data catalog, which lists datasets across a company, and from a semantic layer, which translates database fields into business terms for reporting. For product data, the metadata layer is mostly your attribute model, explained in the attribute modeling guide.
Why Metadata Layer matters for e-commerce
A webshop filter, a marketplace feed and an ERP integration all read the same product fields. If each system guesses what a field means, small differences add up: a size in centimeters on one channel and inches on another, or colors that do not match any filter value. A clear metadata layer makes those meanings explicit once. New team members know what to fill, integrations map fields without guesswork and quality checks know what a correct value looks like. It also makes it easier to add a channel, because you can compare its requirements with the fields you already define.
Examples of Metadata Layer
- 1Attribute: Weight, Type: Number, Unit: kg, Rule: Required for shipping
- 2Attribute: Color, Type: Value list, Values: Black, Navy, Red, Used in: Webshop filters and feeds
- 3Attribute: Screen size, Type: Number, Unit: inch, Applies to: Category Televisions only
- 4Relation: Accessory of, From: Charging cable, To: Phone model, Used in: Cross-sell blocks
How WISEPIM Helps
- Attribute management: define attributes with types, units and value lists, and review them on the Attribute values page.
- Product families: decide which attributes apply to which group of products.
- Category map: map your own categories to the Google product taxonomy and channel categories.
- Quality Guard rules: check product data against the rules you set in your attribute model.
Common mistakes with Metadata Layer
- Using free text for fields that need a value list, such as color or material.
- Storing units inside values, such as 2.5kg, instead of in a separate unit setting.
- Creating near-duplicate attributes, such as Colour, Color and Kleur.
- Defining fields without an owner or description.
- Changing a field's meaning without telling the teams and integrations that use it.
Tips for Metadata Layer
- Write a one-line definition for every attribute.
- Use value lists wherever shoppers filter.
- Store numbers and units separately.
- Name one owner per attribute group.
- Compare your model with each channel's required fields before you add a channel.
Trends around Metadata Layer
- AI that reads attribute definitions to fill and check product data.
- Shared industry models such as ETIM and GS1 attributes.
- AI shopping assistants that depend on well-defined product attributes.
- Data contracts between teams that describe fields and their rules.
Tools for Metadata Layer
- WISEPIM: PIM with attribute management, product families and Quality Guard rules.
- Akeneo: PIM with a structured attribute and family model.
- Salsify: product experience platform with property definitions.
- Contentful: headless CMS with content models.
- Collibra: data governance platform with a business glossary and data catalog.
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