UX for Complex Data Design
Tips to help you optimize your design for big data sets
1. Information Architecture is Key
The basic building block of any digital design is the information architecture (IA). Great IA helps people understand what they are looking at, determine what to expect and accomplish their goals.
2. Reduce Chaos with Grids
Organizing elements in a user interface to a consistent, logical grid will go great lengths in improving user experience. The use of structure, alignment and a page layout can improve functionality, aids clarity and overall improves discover-ability.
3. Think Through User’s Mental Models
A good design best practice for dealing with large data sets is to align the conceptual model expressed by your interface with your user’s mental model as closely as possible.
In online experiences, products and services, users expect a certain sequence of events based on both past encounters and their desire around what the experience should be.
4. Manage Complexity with Progressive Disclosure
Progressive disclosure is the most common methods of managing complexity. The idea is that cognitive load can be reduced by hiding less frequently used elements behind an addition action — such as a hover, click or activated state.
When using progressive disclosure, it is crucial to accurately determine which elements are frequently and infrequently used in order to determine what needs to be shown on a screen.
Conclusion
Carefully consider what data and how much users need or want to see. Basic design principles still apply regardless of the size of your data set, so make you understand your user needs (with data to back it up) and guide users toward their tasks as seamlessly as possible.
Remember to use the framework of the user’s mental models as a foundation for structuring the user interface’s content and layout.
