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Data Visualization Techniques and Graph/Chart Views
Experience Design Challenges n Data Visualization Techniques
Most users come to an application to use a small subset of features. Designers can assist the user by displaying those key features, which helps to de-clutter the UI and emphasizes the basic or recommended functionality of the product. Specialists can still access the more advanced features via keyboard commands or the menu, but those actions can take a backseat to buttons, visuals, or links that get used daily.
For example, when designing the report and dashboard creation widget of a business analytic program, a designer has the choice to display an array of colors or default to gradients of the same color. While it may seem more “feature rich” and desirable to offer all colors, this is setting your user up for a bad end result.
Usage of Data To An Advantage
In the business intelligence world, users gain insights about their own product by combining and analyzing different data sources, such as data from a CRM with Google Analytics, to see how their customers are using the product.
When we’re designing BI software, we use those same techniques. Collecting and analyzing data from support forums and documentation page visits help us better understand which aspects of a current product are creating problems for users, and where the product needs to change or grow. With that knowledge garnered from bug reports, customer issues, and feature requests, we are better equipped to filter bugs, prioritize development, and improve the R&D workflow.
Data Visualization MUST be Interactive
Data visualizations attempt to present information in a way that helps the brain to understand correlations, trends, and outliers at a glance. A static graph illustrates one piece of information well, but the user cannot garner any other answers from it. When reports and dashboards are interactive, users can drill down into different segments, explore a specific correlation, and glean insights. In this way, users can easily analyze data, zoom out to the bigger picture and capture the smallest detail. Exposing users to the tools they need to run visualizations directly on the data is an incredible UX boost.
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