Data Harmonization is the process of making data from different sources consistent enough to be combined, compared, or analyzed together. It can involve standardizing formats, units, naming conventions, categories, and field structures while preserving the meaning of the original information. The goal is to resolve differences that would otherwise make datasets difficult to use together.
For example, one system might record dates as DD/MM/YYYY while another uses MM/DD/YYYY, or different systems may use different labels for the same product category. Harmonization aligns these variations so the resulting data can support reliable reporting, analytics, and integration. It is commonly used alongside data integration, data transformation, and data quality processes.
