Data quality assessment process is essential to ensure reliable analytical outcomes. This process depends on human supervision-driven approaches since it is impossible to determine a defect based only on data. Visualization systems belong to a class of supervised tools that can make data defect pattern visible. However, their considerable design knowledge encodings and imple- mentations provide little support design to data quality visual assessment. To cover this gap, this work reports the design approach of V is4DD visualization system based on patterns of data defects structures and assessment tasks. An exploratory case study used this web-based system to explore which and how visual-interactive properties facilitate visual detection of data defect.