Standards

Core Data Quality Dimensions Matrix

Similarly to the means of measurement of physical objects (E.g. Length, width, weight, etc.), Data Quality dimensions are measurable features or characteristics of data. They are used to understand the quality of data.

The six dimensions for Data Quality defined as standard in the context of the enterprise Data Quality Framework are the following:

Controls core dimensions matrix

These dimensions are recognized as six primary dimensions for data quality assessment used by majority of organizations (1).

Additional Data Quality Dimensions Matrix

The following set of Data Quality Dimensions can optionally be used to complete the core dimensions provided above.

Controls additional dimensions matrix

Data Quality Controls Requirements Matrix

The following Matrix provides guidelines on where Data Quality Controls should be applicable based on Datasets overall Data Quality Expectations which are tied to Business Impact:

Controls requirements matrix

Data Quality Controls Requirements Inventory

The following form is the template proposed to identify required Data Quality Controls implementation for Datasets on the basis of the Definitions provided in “Key Assets” This template is meant to be completed by BDOs for their respective Business Area / Business Domain.

  • Instructions for completing the form (*)

For each Dataset, please provide the expected information in the associated Columns:

    1. Provide the identification information as described below for Section “Dataset Identification”

    1. Provide the Expected Data Quality Levels on the basis of what was provided in “2.2-Bus. Impact Level Class.” tab

    1. Fill in the Data Quality Controls Requirements columns on the basis of “Data Quality Controls Requirements Matrix” provided in tab “Key Assets”

Controls requirements inventory

For each criticality level, specific controls are defined to ensure that data sets meet established quality requirements. These controls cover various aspects of Data Quality dimensions (described in the “Core Data Quality Dimensions Matrix”)


Data Quality Controls Requirements Matrix

The following Matrix provides guidelines on where Data Quality Controls should be applicable based on Datasets overall Data Quality Expectations which are tied to Business Impact:

Controls requirement matrix

Best practices to define Data Quality Controls

The following table outlines various categories of data quality rules, specifying their requirements and providing examples to ensure clarity and consistency in data management practices. Each rule aims to enhance data quality by addressing syntax, scope, threshold, completeness, validity, and precision constraints.

Controls templates SDAN

Data Quality Controls templates

Please refer to the Data Quality Framework documentation center.


References:

(1) DAMA UK - The six primary dimensions for data quality assessment