Steps of Data Visualization
1. Data Collection and Preparation:
Get the right information in order and process it for visualization by reducing outliers, sorting, and selecting only needed information.
2. Choosing the Right Visualization:
Choose the best type of visualization according to the nature of the data and the things you want to inform the audience about.
3. Designing the UI:
Incorporate the chosen visualization into the interface in a way so it will fit into the design elegantly while considered its usability.
4. Testing and Iteration:
Have users test the visualization to improve its usability and repeat the iterations if need be, utilizing their input to enhance the graphs.
Data Visualization in UI
Data visualization has become increasingly dominant in the user interface (UI), and this technique become even more effective in fulfilling these purposes. Through the encapsulation of raw data into visual forms, information even of complex type becomes intuitive to users and the quality of their experience is improved. Data visualization can be applied in the UI of digital products or applications through the visual forms of data that are used in UI. It refers to using data to understand and tell the story of different datasets using visualizations like graphs, charts, maps, and diagrams. Through these visualizations, these insights, patterns and trends hidden within the data come out as easily comprehensible to the users who in turn possess the required knowledge to make crucial decisions.
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