Towards Understanding Visualization Impedance Mismatch

User interfaces serve as the primary interaction point between users and software systems, yet designing intuitive and effective interfaces remains a challenge, particularly when visualizing complex technical data. In this study, we introduce the concept of visualization impedance mismatch, which describes the misalignment between the way data and mechanisms are visualized and the mental models users employ when interacting with a system. Through a case study involving ten developers, we identify key difficulties in UI design and extract $\mathbf{1 5}$ user interface patterns aimed at reducing this mismatch. These patterns provide structured solutions to common UI design challenges, addressing issues such as feedback mechanisms, action tracking, contextual messaging, and error prevention. We further discuss internal and external threats to validity when identifying such patterns. Our findings contribute to a deeper understanding of visualization challenges in software design and offer practical guidelines for developers seeking to improve user experience in data-heavy applications.