AttributesDAMA: 27

Equivalence

The degree to which attributes stored in multiple datasets are conceptually equal.

Created: 10/30/2025
Business Impact
Positive Impacts
  • •Simplified data integration and mapping between different systems or datasets.
  • •Reduced ambiguity when attributes representing the same concept have different names or formats.
  • •Improved consistency in understanding and using conceptually similar data across the organization.
  • •Facilitates creation of a common business vocabulary and semantic layer.
Negative Impacts (if poor quality)
  • •Increased complexity and cost in data integration due to mismatches in attribute definitions.
  • •Risk of misinterpreting or incorrectly joining data if conceptually equivalent attributes are not recognized.
  • •Inconsistent reporting or analysis if different terms are used for the same underlying business concept.
  • •Barriers to establishing a shared understanding of data across business units.
Technical Description

%

Examples
Good quality vs poor quality indicators
Good Quality Examples

Logistics: Both the terminal planning system and the execution system use the attribute 'VesselVoyageID' with the same definition, data type, and format.

Product Management: All systems that store product dimensions (length, width, height) use the same attribute names (e.g., 'ProductLengthCM', 'ProductWidthCM', 'ProductHeightCM') and consistently use centimeters as the unit.

HR: The attribute 'EmployeeStartDate' has the exact same meaning (first day of employment) and date format across the HRIS, payroll, and benefits systems.

Poor Quality Examples

Logistics: One system uses 'CustID' (integer, primary key) while another system uses 'CustomerIdentifier' (alphanumeric string, business key) for the same customer concept, making automated joins difficult.

Product Management: 'ProductWeight' in the catalog system is in kilograms, while 'Item_Wt' in the shipping system is in pounds, for the same product attribute.

HR: 'Employee_Status' in one system might use codes ('A', 'T', 'L' for Active, Terminated, Leave) while another uses full text ('Active', 'Former Employee', 'On Leave').

Local Network
Quick Stats
Dependent KPIs0
Improvement Standards3
CategoryAttributes
API Access
GET /api/dq-dimensions/8378ebfa-ef53-4ef1-bf24-1cd2571d1b07