Data valuesDAMA: 41

Precision (1 - Recording Accuracy)

The degree of accuracy with which data values are recorded or classified.

Created: 10/30/2025
Business Impact
Positive Impacts
  • •Data recorded with sufficient detail and exactness to meet business or analytical requirements.
  • •Accurate calculations and measurements based on precisely captured values.
  • •Improved ability to distinguish between small but significant variations in data.
  • •Better fit for applications requiring high levels of detail (e.g., scientific research, engineering design).
Negative Impacts (if poor quality)
  • •Loss of information if data is recorded with insufficient precision (e.g., rounding errors obscuring true values).
  • •Inaccurate calculations or analysis if measurements are too coarse.
  • •Inability to detect subtle changes or make fine distinctions in data.
  • •Unsuitability of data for tasks requiring high precision.
Technical Description

Depends on data or metadata

Examples
Good quality vs poor quality indicators
Good Quality Examples

Logistics: Measuring vessel draft to the nearest centimeter, providing the necessary precision for safe navigation and berth planning.

Manufacturing: Using calibrated instruments to measure product weights to the nearest gram, as required by quality control standards.

Finance: Recording financial transactions with precision to the smallest currency unit (e.g., cents, pence) as defined by accounting standards.

Poor Quality Examples

Logistics: Recording container temperatures only to the nearest 5 degrees Celsius when the cargo requires monitoring to +/- 0.5 degrees.

Manufacturing: Measuring component dimensions only to the nearest millimeter when engineering tolerances require micron-level precision.

Finance: Rounding all currency transactions to the nearest dollar when cents are significant for accounting.

Local Network
Quick Stats
Dependent KPIs0
Improvement Standards4
CategoryData values
API Access
GET /api/dq-dimensions/9881bcca-9cc9-4c6e-af74-58dba8f77377