As companies are leaning on the convergence of Big Data and Business Intelligence (BI) to make more informed and cost-effective decisions, it is becoming increasingly important to ensure data is presented in a more effective and efficient way – enter the rise of data visualization. From infographics to heat maps, data visualization is a great tool for showcasing complicated data or displaying important inferences in a visual format, which can be easily digested for visual learners.
Data visualization, however, requires planning and proper execution to achieve the expected outcomes. The challenge arises in how data visualization aides are created and presented, and how to provide proper interpretation. Here are six tips for using data visualization effectively when presenting big data results and complex data sets.
1. Think Like the Reader/User
Consider the audience and consider what they want to know and already know. How and when will they see and use the display, and what should they know before viewing? The final design should not require additional knowledge, and it should be fairly simple to map out the direction of the images and follow a “visual line of cues.” Data visualization should result in a sensory process and excite the reader, not confuse.
2. Less Can Be More
It is not possible to show every single piece of data in one infographic or in one heat map. Instead, figure out the main data points and identify the support information. Place priority on the outcomes and results that are the focus, and use the remainder of the space to provide the support information. This can be accomplished by using varying sizes and colors placing emphasis on the larger elements and bolder colors.
3. Keep It Simple
If there is data that extends to many decimal places, shorten it. If the number has six zeros, write it out (ie. $1 Million). Avoid using too many crazy graphics or movement and stick to what the user needs and how to stimulate them without distracting them.
4. Suggest Specific Action
If there is a specific action that should come from ingesting the design, be sure that action is obvious. For example, if a heat map shows the most dense areas of crime in a city and a police force is using it to assign positions, the “red” areas indicating higher crime rates will instantly attract attention and help to quickly identify the trouble spots. The action would be that the police force places more officers in that location and can figure it out based on crime instances and area size.
5. Make It Interactive
If the goal is to show how one factor may affect another, an option can be to use an interactive infographic that invites the user to enter specific information, then generates results based on the initial entry. There is a New Zealand based company, MahiFX.com that launched by creating an interactive infographic, which allowed users to enter their yearly salary and compared it to how quickly super forex trader, John Paulson, could make that same amount by trading. It was considered powerful digital strategy that made a clear point and the campaign received accolades for their use of interactivity to personalize the result and make a point/drive action.
6. Use Layers of Data
If the data visualization display is virtual and has a user interface, keep the data layered. When trying to show big data sets, this can be a key component to getting a lot of information out there, but avoiding overload. This can include allowing the user to zoom in to see more specific detail. Think about Google maps and how you can view the basic information about a specific area, but as you zoom in, you see more specific data that drills down to street and building level – this is an example of layering.