AttributesDAMA: 28

Granularity (Attributes)

The degree to which a single characteristic is subdivided in attributes.

Created: 10/30/2025
Business Impact
Positive Impacts
  • •Enables precise data capture and more detailed analysis.
  • •Improved flexibility in querying, filtering, and aggregating data based on specific sub-components.
  • •Better support for complex business rules that depend on fine-grained attribute details.
  • •Enhanced data quality as validation can be applied to more specific data points.
Negative Impacts (if poor quality)
  • •Loss of detail, limiting the depth of analysis and insight generation (e.g., cannot analyze by city if only full address is stored).
  • •Difficulty in applying specific business rules or validations if attributes are too broad.
  • •Increased complexity in parsing or splitting combined attributes for specific uses.
  • •Inability to answer specific business questions requiring finer detail.
Technical Description

Story

Examples
Good quality vs poor quality indicators
Good Quality Examples

Logistics: 'Address' is broken down into separate, well-defined attributes: StreetAddress, City, PostalCode, State, Country.

Contact Management: 'FirstName', 'MiddleName', 'LastName' are stored as distinct attributes.

Event Logging: 'EventTimestamp', 'EventType', 'UserID' are stored as individual attributes for easier filtering and analysis.

Poor Quality Examples

Logistics: A single 'Address' attribute in the customer table holds the entire address: Street, City, Postal Code, and Country, making it hard to query by city.

Contact Management: A 'FullName' attribute stores first name, middle name, and last name together.

Event Logging: A single 'EventDetails' attribute contains timestamp, event type, and user ID concatenated together.

Local Network
Quick Stats
Dependent KPIs0
Improvement Standards0
CategoryAttributes
API Access
GET /api/dq-dimensions/58f8a033-d940-47be-9df1-01ac5e26a3bd