Systems are becoming more interconnected and capable of relaying qualitative and, increasingly, quantitative data at varying frequencies and levels of complexity. Information visualization becomes even more vital in this case.
Simply put, information visualization is the process of graphically expressing abstract data such that the viewer can comprehend both the data and its underlying connections.
Dashboards and Businesses
Business Intelligence Dashboards enable business owners, managers, team leaders, and any other stakeholder with access to them to track and forecast performance at the individual, department, or company level, depending on their access level. In this sense, business dashboards may be used to track anything ranging from the broad, such as a company's overall success, to the specialized, such as a product's sales performance.
A dashboard with a fantastic user experience will not only allow you to monitor all areas of your company's health and stability, but it will also have a direct influence on staff productivity.
Dashboard design: 6 things every UX designer should know
Below are six things that you as a UX designer should know:
Show insights, not just data
Designers frequently mix up insights and facts. A user isn't only interested in looking at the data in a pretty way; they want to see what they could do with it. For example, suppose I'm designing a portion of a dashboard for a recruiting agency where the CEO examines the number of people employed. In that case, a simple method may be to display 'Total applications,' 'People hired,' 'Application in process,' and 'Applications rejected.'
However, providing merely the statistics would probably not benefit the user. The insight that would be most useful is to highlight that the number of persons employed has increased/decreased compared to the previous month.
Visualize data the right way
The content of dashboard UX must be structured such that it is the most accessible and beneficial to the consumers. It's usually best to follow some reasoning or a concept that industry leaders have used since this will improve your chances of creating a superior design.
The Inverted Triangle, sometimes known as the bottom line upfront in journalism, is based on a similar premise (BLUF). According to this idea, news content is separated into three categories, decreasing order of importance. The most critical information is at the top, an overview is in the center, and background information is at the bottom, allowing a user to go deep.
Dashboard UX should follow the same pattern. The most important and high-level insights appear first, followed by trends related to these insights, and finally, the granular details that only a few people would wish to investigate.
Understand the user and the psychology
Most designers conduct the necessary research to understand the user in terms of demographics, competitive analysis, user personas, and other factors, but user psychology is one of the most important factors to consider when developing dashboards.
Dashboards aren't designed to show you everything right away. Too much knowledge can lead to Analysis paralysis, which is the over-analysis (or over-thinking) of a problem to the point that no decision or action is made, thus paralyzing the conclusion.
Dashboards are designed to connect you to more information. Progressively reveal knowledge. Allow the visitor to drill down more if he desires by displaying a snippet of the most significant data item upfront.
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Let’s create progress together.
Follow design principles — principles of interpretation
The Gestalt school of Psychology investigated human perception through a series of studies in the early 1900s. It discovered six principles for easy information interpretation in a dashboard UI design:
- Similarity: Our brains will associate similar items in shape, size, color, or orientation, even if they aren't grouped.
- Proximity: Our brains may group several things or shapes close to each other.
- Completion: When a figure is missing, our brains create regions to fill in the gaps.
- Connection: A pair or group of objects or shapes linked by a line will be noticed.
- Enclosure: When a boundary encloses items, we interpret them as belonging to a group.
- Continuity: We perceive aligned objects to be a continuous body or series.
Don't measure everything on the same scale
While reviewing various dashboard UI designs, we noticed that some people combined comparable graphs to make the design more beautiful and symmetrical, even though not every data piece is designed to be displayed in a graph.
It's not a good idea to employ many visualizations simply because you can. Consider scalability, and determine if the data in the graph will remain the same or whether more respondents/dates/figures will be added in the future.
Dashboard Design Guidelines
Dashboard UI design should...
Demonstrate the significance of the underlying data
The user must grasp the data supplied in dashboard UX right away. This may be accomplished by using clear statistical and verbal explanations and proper labeling and logical grouping of relevant visualizations.
Support the intended user's goals and objectives
The dashboard's vocabulary and complexity should be appropriate for the target user. Using highlighting and alerts, the user's attention must be brought to certain aspects of interest.
Summarize data
When a user accesses the dashboard, the dashboard designer must make sure that the most relevant information is immediately visible. This should ideally be delivered in the form of a summary.
Make the best possible use of the available space
Following point 1 does not inevitably imply that the available screen real estate is being utilized to its full potential. This is because the visualizations may simply be shrunk in size and crammed onto a single screen. This, however, is not a good habit. Remove any non-data-carrying components, such as frivolous photos.
Provide a way to go further into the information
The user must be able to study any points of interest in the summarised data seamlessly. This will aid them in better comprehending the data and investigating the causes of abnormalities (a sudden drop in sales, for instance).