Data Steward

What is Data Steward?

A data steward is the person responsible for the quality of a specific set of data. A data steward defines what correct data looks like, checks that it stays complete, accurate and consistent, fixes errors at the source and is the go-to contact when others have questions about that data. In e-commerce the role is often a product data steward: someone who owns the product catalog, or one part of it, such as a category, a brand or a language. They decide which attributes are required, which values are allowed and who may change what. Data stewardship is the practice of doing this work, while data governance sets the policies and roles around it. A data owner is accountable for the data; the steward does the daily care. The data governance guide shows how the roles fit together.

Why Data Steward matters for e-commerce

Product data passes through many hands: suppliers, buyers, content writers, translators and marketplace managers. Without one clear owner, everyone assumes someone else checks the details. Errors in sizes, prices or compliance fields then reach the webshop and marketplaces, where they cause returns, rejected listings and support questions. A data steward closes that gap. They set the rules per category, review incoming supplier data, follow up on quality reports and decide how conflicts are solved, for example when two sources give a different weight for the same product. The role also makes growth manageable. Adding a new channel, language or product range means new requirements. A steward who knows the data model and the channel rules can translate those requirements into attributes and checks, so the catalog stays usable as it grows.

Examples of Data Steward

• 1Role: Product data steward Fashion, Owns: Size, fit and material attributes, Weekly task: Review products that fail completeness checks
• 2Role: Data steward Supplier onboarding, Owns: Incoming supplier files, Task: Map supplier columns to the attribute model and reject files with missing GTINs
• 3Role: Language steward German, Owns: German product texts, Task: Check translated terms against the glossary before publishing
• 4Role: Channel steward Marketplaces, Owns: Category mapping and channel-required fields, Task: Fix listings that a marketplace rejected

Tips for Data Steward

• Assign stewards per domain and write down which data each one owns.
• Turn each quality rule into an automated check so the steward reviews exceptions, not every product.
• Give the steward a short weekly list of the products that matter most, such as best sellers with errors.
• Agree on how conflicts between sources are decided before they happen.

Trends around Data Steward

• Stewards reviewing AI-generated content instead of writing every text themselves.
• Automated checks that send stewards only the exceptions instead of full reports.
• Stewardship split by domain, such as category, language or channel, instead of one central team.
• New compliance data, such as EU product passport fields, added to the steward's scope.

Tools for Data Steward

• PIM systems such as WISEPIM, Akeneo and Salsify, where stewards set validation rules and review product data.
• Data governance platforms such as Collibra, which manage glossaries, ownership and policies.
• Data quality tools such as Informatica Data Quality, which profile and monitor data.
• Spreadsheets and shared documents, which work as a start for logging rules and owners.

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