From Qlikview Winning Dashboard Link
Think About the Data Before the Dashboard
Before you even begin to build your dashboard, you must think carefully about the data and how it will be used, says Perrot. It’s absolutely imperative to use accurate, relevant and reliable data: if your numbers aren’t sound, the insight they provide is misleading, and the dashboard isn’t useful.
You also need to organize this data and present it in a way that makes sense. Perrot commonly uses star or snowflake schemas, and this is what he suggests others default to. For most datasets, these models provide the best infrastructure for organizing data and enabling the end user to view it in a variety of different ways.Perrot estimates that 60 percent of the time he spent working on this project went towards brainstorming how the end user would need to interact with the dashboard application. This included ensuring that he had the perfect data model to reinforce expected user behavior and to present the right information quickly, clearly and accurately.
It’s also important to think about how this data will be used. Here are some of the questions Perrot suggests dashboard creators ask business users:
- Which Key Performance Metrics (KPIs) will be most important for the end user?
- What story are you trying to tell through your dashboard?
- Which data supports that story, and illustrates it most clearly for the end user?
- What are the common dimensions of analysis between my different data sources?
- Which data is the user going to click on and interact with?
Develop the Overview Screen First
When looking at the overview screen—the high-level screen that summarizes the dashboard’s most important information—the end user should instantly understand what is wrong with his business (or, in the case of the Challenge, what is wrong with the world).
Perrot recommends building this screen first; when creating “Do You Realize?,” he started with the “Overview” screen. Next, he builds additional screens that will help the user better understand the significance of a given KPI: here, the “Environment” and “Health” screens.
Finally, he builds out a screen that allows the user to compare different data points and build their own analysis. It’s important to work in this order, Perrot says, for a few reasons:
- The overview screen is essentially a high-level summary of the your most important KPIs. If this screen isn’t clear, it means that you don’t know what you want to explore and demonstrate with your dashboard, says Perrot.
- Since it presents all the most important information in one place, the overview screen is where the majority of your end user’s business questions will arise from. You have to imagine all the questions the end user might have after seeing the dashboard, and develop the other views to help him answer those potential questions.
- Once the overview is clear, Perrot says, the rest of your application and the story it tells will come naturally. Without having this first, you’re likely to develop overly complex, inconsistent screens—or worse, screens without relevance to the end user’s business needs.
Create a Dashboard That’s Both Attractive and Informative
As with so many things in life, first impressions are crucial when it comes to your dashboard. A well-designed, attractive dashboard is more compelling to the end user—as long as it’s also functional. Your design choices can also inform your data, indicating important things to the reader that help them understand the greater message.
→ Use color to convey change. Change over time is a key component of almost any dashboard. According to Perrot, the best way to help the end user quickly visualize this is to use color coding. Assigning colors to trend lines or data points can tell you something about the data: for example, green means the measure is moving in a positive direction; red means it’s not.
Software Advice > Blogs > Plotting Success
FROM TABLEAU GUIDE
The following guidelines will help you design great dashboards:
• Place the most important view at the top of your dashboard, or in the upper
left corner. When looking at a dashboard, your eye is usually drawn to that
corner first.
• If your visualization has chained interactivity (the first view filters the next view
which filters the last view, etc.), structure them from top to bottom and left to
right. That way, the final view to be filtered will be on the bottom, or bottom right.
• Unless there is an absolute need to add more, limit the number of views in
your dashboard to three or four. If you add too many views, the big picture can
get lost in the details. Remember, you can always use multiple dashboards to
tell one story!
• Avoid using multiple color schemes in a dashboard—unless there are natural
and independent color schemes in your data.
• If you have multiple filters, try to group them together with a layout container.
A light border around them gives a subtle visual cue that they have shared
features. The right, top, and left sides of the dashboard are all great places to
put your filters.
• If a legend applies to all of your views, place them together with all of your
filters. If a legend applies to one or a few more views, place it as close to
those views as possible.
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