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Data Stewardship

Data management1/5/2026Intermediate Level

Data stewardship involves the responsibility for managing, overseeing, and ensuring the quality and integrity of an organization's data assets.

What is Data Stewardship? (Definition)

Data stewardship is the practice of assigning specific people or teams to manage a company's data assets. These data stewards act as caretakers who make sure information stays accurate, organized, and secure. They bridge the gap between technical IT teams and the business users who need reliable data for daily tasks. A data steward handles several key responsibilities: * Setting clear rules for how to enter and format data * Fixing errors or filling in missing information * Approving changes to important records * Writing definitions so everyone understands what specific data fields mean * Ensuring the company follows privacy and legal regulations This role helps businesses maintain high-quality information across all systems. By having dedicated stewards, companies can trust their data when launching new products or analyzing sales trends. Tools like WISEPIM help these teams by providing a central place to monitor and update product information efficiently.

Why Data Stewardship is Important for E-commerce

Data stewardship is the process of keeping product information reliable for online shoppers. High-quality data builds trust and helps the business run better. If product details are wrong or prices are old, customers get frustrated. This often leads to more returns and lost revenue. Data stewards make sure product info is correct on every page and in every ad. They catch mistakes early so the customer never sees them. This constant care reduces errors and helps managers make decisions using facts they can trust.

Examples of Data Stewardship

  • 1A PIM manager acts as a data steward for product descriptions. They ensure all new content follows brand rules and stays free of errors.
  • 2An IT specialist serves as the data steward for technical specifications. They verify that all data values use the correct formats and units.
  • 3A marketing team member manages media assets as a data steward. They make sure images and videos are high quality and link to the correct products.

How WISEPIM Helps

  • WISEPIM lets you assign specific roles to team members. This makes it clear who is responsible for each part of your product data.
  • Data stewards can create quality rules directly in WISEPIM. These rules help find and fix errors before they cause problems in your store.
  • WISEPIM includes tools to track data changes and manage approvals. This helps stewards ensure all product information meets your company standards.

Common Mistakes with Data Stewardship

  • Failing to assign specific people to manage data. This makes it unclear who is responsible for fixing errors.
  • Skipping the creation of clear rules for data. Without these standards, information becomes messy and inconsistent across the company.
  • Treating data management as a one-time task. If you do not check data regularly, the quality drops as information becomes outdated.
  • Forgetting to give staff the right tools or training. Without support, employees cannot manage data effectively.
  • Managing data in a bubble. Data stewardship works best when it connects to the rest of the business and its daily tasks.

Tips for Data Stewardship

  • Assign clear tasks and areas of responsibility to each data steward. This prevents confusion about who owns specific data.
  • Create simple rules and definitions for your data. Make sure everyone in the company can find and understand these guidelines.
  • Set up a system to check data quality regularly. Use specific metrics to find and fix errors before they cause problems.
  • Offer ongoing training and the right tools to your data stewards. This helps them manage data accurately as your business grows.
  • Connect data management tasks directly to your PIM system and daily work. This makes high-quality data a natural part of every employee's routine.

Trends Surrounding Data Stewardship

  • AI and Machine Learning integration for automated data quality checks, anomaly detection, and data enrichment, reducing manual effort for data stewards.
  • Increased focus on data ethics and privacy, with data stewards ensuring compliance with evolving regulations like GDPR and ethical use of data in AI applications.
  • Shift towards proactive data governance, where data stewards leverage automation to prevent data issues rather than reactively resolving them.
  • Adoption of Data Mesh architectures, localizing data stewardship responsibilities within domain-specific teams for greater agility and ownership.
  • Emphasis on sustainability data management, with data stewards ensuring the accuracy and consistency of environmental and social impact data for reporting and compliance.

Tools for Data Stewardship

  • WISEPIM: A PIM solution that centralizes product data, enabling data stewards to define, enrich, and validate product information for consistency and quality across channels.
  • Collibra: A leading data governance platform offering data cataloging, data lineage, business glossary, and data quality capabilities to support data stewards.
  • Akeneo: An open-source PIM system that provides workflows for data enrichment, validation, and approval, crucial for data stewards managing product information.
  • Salsify: A Product Experience Management (PXM) platform combining PIM, DAM, and syndication, helping data stewards manage product content across diverse sales channels.
  • Informatica Data Governance & Compliance: A comprehensive suite of tools for data catalog, data quality, and master data management, empowering data stewards in large enterprises.

Related Terms

data governanceproduct data qualitydata validationmaster data management mdmproduct data management

Also Known As

Data custodianData ownerData governance role