Who should own address data quality, and what processes ensure it?

Who should own address data quality, and what processes ensure it?

• A. End users
• B. IT admins only; enforce governance policies, regular cleansing, data quality rules, and an issue-tracking workflow for improvements.
• C. No ownership or process
• D. Data stewards or product owners; enforce governance policies, regular cleansing, data quality rules, and an issue-tracking workflow for improvements.

Answer: (D)

Clear ownership of address data quality rests with data stewards or product owners, because they are the roles responsible for the data’s meaning, use, and accountability across the organization. They set and enforce the standards that define what "good" data looks like, and they stay involved as data evolves. They enforce governance policies to create consistent rules and responsibilities, run regular cleansing to remove duplicates and correct errors, and apply data quality rules that specify validations, formats, and required fields. They also manage an issue-tracking workflow to capture quality problems, prioritize them, assign remediation tasks, and track improvements over time. This combination creates a accountable, repeatable process that keeps address data reliable for downstream systems and decision-making. End users alone often generate or rely on data without the authority to enforce standards; IT admins alone typically implement systems and policies but don’t own the data’s meaning and long-term quality ownership. No ownership or process leads to unclear accountability and inconsistent data.

Clear ownership of address data quality rests with data stewards or product owners, because they are the roles responsible for the data’s meaning, use, and accountability across the organization. They set and enforce the standards that define what "good" data looks like, and they stay involved as data evolves.

They enforce governance policies to create consistent rules and responsibilities, run regular cleansing to remove duplicates and correct errors, and apply data quality rules that specify validations, formats, and required fields. They also manage an issue-tracking workflow to capture quality problems, prioritize them, assign remediation tasks, and track improvements over time. This combination creates a accountable, repeatable process that keeps address data reliable for downstream systems and decision-making.

End users alone often generate or rely on data without the authority to enforce standards; IT admins alone typically implement systems and policies but don’t own the data’s meaning and long-term quality ownership. No ownership or process leads to unclear accountability and inconsistent data.