The six data quality dimensions — and how to measure them in Salesforce
Completeness, validity, consistency, uniqueness, timeliness, accuracy. These six dimensions are how you turn “our CRM data is messy” into something specific enough to fix. Here’s what each one means, with a real Sales Cloud example — and how they combine into a single score you can act on.
What a “data quality dimension” actually is
A data quality dimension is one specific way data can be good or bad. “Bad data” is too vague to fix; “this Account is a duplicate” or “this Opportunity has no close date” is specific enough to act on. The six dimensions below are the standard lens data teams use — and every one of them shows up plainly in Salesforce.
Six ways your Salesforce data can let you down
Completeness
Are the fields that matter actually filled in? In Sales Cloud: an Opportunity with no close date, or a Lead with no email, can’t be worked or forecasted.
Validity
Does the value fit the rules and format it should? In Sales Cloud: a phone number sitting in an email field, or a stage value that no longer exists in your sales process.
Consistency
Does the same fact agree everywhere it appears? In Sales Cloud: an Account’s industry disagreeing with the same company recorded on a related Contact.
Uniqueness
Is each real-world thing stored exactly once? In Sales Cloud: the same company saved as three Accounts inflates coverage and splits activity history.
Timeliness
Is the data current, or has the world moved on? In Sales Cloud: a Contact who changed jobs months ago is a dead lead dressed up as a live one.
Accuracy
Does the data match reality? In Sales Cloud: a deal marked Commit that the customer has already postponed is the most expensive kind of inaccurate.
One score, not six arguments
Measured one at a time, the dimensions are an academic exercise. Measured together, per object, they become a number a team can own. ForecastGuard scores each of your five core Sales Cloud objects — Leads, Contacts, Accounts, Opportunities and Cases — across all six dimensions to produce a DQ Health Score Card, then ranks what to remediate first. See the bigger picture in the Salesforce data quality guide, or see the scorecard in the interactive preview →
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