Data categories are groupings of data with common characteristics or features. They are useful for managing the data because certain data may be treated differently based on their classification. Understanding the relationship and dependency between the different categories can help direct data quality efforts.
For example, a project focused on improving master data quality may find that one of the root causes of quality problems actually comes from faulty reference data that were included in the master data record.
By being aware of the data categories, a project can save time by including key reference data as part of its initial data quality assessments. From a data governance and stewardship viewpoint, those responsible for creating or updating data may be very different from one data category to another.
Danette McGilvray explains how an understanding of the relationships and dependencies between different data categories can help direct data quality efforts. The article is based on content from her upcoming book, Data Quality Projects: Ten Steps to Quality Data and Trusted Information.