This research proposes a new approach to data quality evaluation comprising 3 aspects: (1) data object definition, which quality will be analyzed, (2) quality requirements specification for the data object using Domain Specific Language (DSL), (3) implementation of an executable data quality model that would enable scanning of data object and detect its shortages. Like the Model Driven Architecture (MDA) the data quality modelling is divided into platform independent (PIM) and platform-specific (PSM) models. PIM comprises informal specifications of data quality, PSM describes implementation of data quality model, thus making the data quality model executable. The approbation of the proposed approach provided at least 3 advantages: (1) a graphical data quality model allows definition of data quality by non-IT professionals, (2) the data quality model is not related to the information system that has accumulated data to be analyzed, i.e., this approach allows analysis of an “external” data, and (3) the quality of the data can be described in two abstraction levels - informally using natural language or formally including executable program routines and/or SQL statements.