Why a Policy Matters
Without a written policy, data quality standards exist only in the minds of the people who care about them. When those people leave, change roles, or simply have a bad week, the standards go with them.
A data quality policy makes standards explicit, shared, and durable. It's the governance document that makes a data quality program sustainable.
What a Policy Is Not
A data quality policy is not a technical specification. It's not a list of validation rules for your database. It's not an IT document.
Sohovi lets you set up validation rules for any column and instantly see which rows fall outside them — no code or SQL required.
A policy is a statement of organizational intent: what quality standards the organization commits to maintaining, who is responsible, and how compliance is measured and enforced.
The Core Components of a Data Quality Policy
1. Purpose and scope Why does this policy exist? What data does it cover? (All customer data? All financial data? Specific systems?)
2. Data quality standards For each data domain or system covered: what are the minimum acceptable quality levels? This should reference specific dimensions: "Customer email fields must be 95% complete and 99% valid."
3. Roles and responsibilities
- Who is responsible for each data domain? (Data owners)
- Who maintains the system and technical standards? (Data stewards, IT)
- Who ensures compliance? (Data governance team or appointed function)
- Who approves exceptions to standards?
4. Measurement and reporting How often is quality measured? Who reviews the results? What report format is used?
5. Issue management How are quality issues reported? Who handles triage? What are the resolution SLAs for critical vs. non-critical issues?
6. Consequences and accountability What happens when standards aren't met? How are persistent issues escalated?
Making the Policy Followable
Keep it short: A policy people don't read is no policy at all. Two to four pages is enough for most organizations.
Be specific: "High quality data" is not a standard. "95% completeness on required fields" is a standard.
Sohovi profiles every column in your dataset for completeness and flags the exact rows where values are missing — free to try.
Review annually: A policy that reflects two-year-old priorities becomes irrelevant quickly. Schedule an annual review.
Get sign-off from leadership: A policy without executive support isn't enforced. Get it endorsed at the right level to give it teeth.
