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Data Quality Management System

The working group has drawn up a draft for a data quality management system, using ISO 9001 as a frame of reference. It can also be called a Data Quality Framework. Below is the diagram of this system. It has 2 objectives (light blue) and 24 elements (dark blue) that contribute to achieving the objectives.

Fact sheets

Fact sheets briefly describe the objectives and the elements of the data quality management system from various perspectives. For each block, it describes what it is, what its purpose is, what procedure applies to manage it, what characteristics it has and what the relationships are with other concepts. The generic knowledge about the objectives and the elements is/will be gathered from different sources.

The following factsheets are available:

  1. Data Quality Policy
  2. Crititcal Data Elements
  3. Data Lineage
  4. Data Quality Rules
  5. Data Quality Monitoring
  6. Data Issues
  7. Data Cleansing

Dimensions of Data Quality

Adapted from Dimension Data by Ashley Jurius on Unsplash

The Data Quality work group has carried out research into definitions of dimensions of data quality. It has collected definitions from various sources and compared them with each other. The working group also tested the definitions against criteria derived from a standard for concepts and definitions: ISO 704.

New in data land is that all dimensions are linked to a ‘data concept’ such as data file, attribute, record and data value. This makes it easier to distinguish between, for example, the completeness of records and the completeness of data values. These data concepts are also provided with standardized definitions.

This research has led to a list of 60 dimensions of data quality and 20 data concepts with standardized definitions. From this list, 12 common dimensions have been selected.

The results of the research are presented in a practical guide in the publication:

A summary of the results of the research is available in:

A complete description of the research and the results is available in:

Tables containing all the concepts and their definitions are online:

  • AirTable. This table contains all dimensions of data quality and a number of views on this table.

Code for Information Quality

The Code for Information Quality is an audit framework for auditing data processes and their end products. This Code is also maintained by the working group.

Contact

Please contact the members of the working group for feedback. It is our aim that our products are relevant and usable for data management & data governance professionals.


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Photo by Ashley Jurius on Unsplash