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Designing Data-intensive Applications — Advice for Interaction Designers
After solo-building a data product, this 30-year design veteran's key lesson: data structure should drive UI, not decorate it.
What: A designer with 30 years of experience shares 10 lessons from solo-building a data-intensive product. Core principle: treat data structure as the interface driver, not an afterthought. Practical tips include learning Python to understand data models, working with realistic data from day one, bridging user mental models with system data models, and designing for empty states.
Why it matters: Signals a shift in design thinking as applications become more data-heavy: designers who can't read code or understand data models will struggle to create effective interfaces.
Original article
A 30-year design veteran shares 10 hard-earned lessons from a year of solo-building a data-intensive product. The core insight is treating data as the interface itself — letting its structure drive page layout, navigation, and interaction rather than decorating a pre-designed shell. Practical tips include learning Python, working with realistic data, bridging user mental models with system data models, and designing thoughtfully for empty states.
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