Optimize your Brain Power with Data Visualization

Data. Data. Data. Everywhere data. The mind numbs at the thought. Daily I am talking with customers discussing their data challenges, where their data resides, and the notion that bringing data together into some meaningful sense is akin to herding cats.

 

The brain processes data at different speeds, and your left and right brain actually focus on different aspects. Data visualization can boost brain power and activate both sides of your brain. According to the Interaction Design Foundation, “Data visualization is the graphical display of abstract information for two purposes: sense-making (also called data analysis) and communication.” It’s possible for the brain to overload with too much information, just like a computer. Visualizing the data can help in keeping, retaining, and analyzing all the information.

#Dataviz can boost brain power and activate both sides of your brain. Click To Tweet

The brain processes data through its perceptive abilities (i.e. the right side, the visual) extremely fast and efficient vs. the way it processes data using its cognitive abilities (i.e. the left side, the thinking). Data visualization is powerful because it shifts the balance between perception and cognition to take better advantage of the brain’s ability to process information. We are able to process visual information much more rapidly than textual information. Optimizing the brain to its fullest is truly a science, but it can be mastered with data visualization.

Visualizing data becomes a necessity when you want quick insight and understanding of large data masses. It also is the best means to easily digest the data, which I’m sure your brain appreciates just as much as mine. Our brains are able to optimize its workload when presented with graphical data vs. the raw data itself.

A number of items to consider that can help to optimize brain power through data visualization:

1. Match the Data to a Visual. When you create visual representations of your data, make sure that it’s relevant to the data you are presenting. Using different charts, images, and colors, you can help make your data more memorable.
2. Be Accurate. Even though you’re using pictures and colors, they need to be accurate in depicting the data. The pie chart or infographic needs to show the right data values and information. Just randomly assigning pictures and colors doesn’t help in representing data. So make thoughtful decisions when it comes to your graphics and imagery.
3. Make it Stand Out. Use colors that highlight the data to help with comparing and contrasting values. However, don’t use colors that can strain the eyes, such as white and yellow or black with blue. Using a grayscale with primary colors are great for data display. The brain will respond well to the color coded data and have an easier time analyzing it.
4. Know How the Brain Works. The Interactive Design Foundation outlines how the brain behaves and responds to data visualization. Guided by the Gestalt Principles and any of the six principles (proximity, similarity, enclosure, closure, continuity, or connection), data visualization can become a more effective method for the brain to digest by shifting from a thinking perspective to a seeing perspective. Applying these principles to data visualization will allow the brain to quickly and more easily process data.
5. Design a Dashboard. Use dashboards to help depict data. Rows of numbers can be overwhelming. Having an interactive dashboard to display multiple metrics, both dynamically and visually, goes a long way in making data easier to read.
6. Keep it simple. Good data visualization takes a complex set of data and makes it easier to understand. It does this through simplifying the perspective and providing ‘big pictures’. When visualizing be careful not to include too many visual stimuli. Remember we’re trying to make it easier to understand and process data.

Let’s look at a few examples of how we can use data visualization to get a quicker and better understanding of our data.

Take the data below. It is showing a set of results for Revenue broken down by State.

State	Revenue	State	Revenue	State	Revenue	State	Revenue	State	Revenue
AL	10604.23	HI	14066.78	MA	9704.79	NM	34454.24	SD	36474.59
AK	10284.74	IA	10835.9	MI	16841.52	NY	41520.7	TN	44573.62
AR	11427.29	ID	16220.72	MN	5631.91	NC	33660.93	TX	32515.69
AZ	14526.93	IL	7460.44	MS	10148.19	ND	36279.79	UT	41664.09
CA	14368.02	IN	6228.67	MO	10369.17	OH	29675.86	VT	34875.9
CO	10081.99	KS	13043.49	MT	14462.75	OK	36366.27	VA	34573.24
CT	41461.55	KY	11491.49	NE	14584.65	OR	35540.94	WA	31216.06
DE	17709.72	LA	13448.77	NV	36492.35	PA	42365.42	WI	37388.47
FL	13830.31	ME	10710.68	NH	41769	RI	34325.1	WY	38545.32
GA	11278.7	MD	10553.76	NJ	39210.82	SC	36371.77	WV	37223.59

 

My brain hurts a little bit just looking at it. Especially, considering what I really want to know from this dataset – which states fall below the revenue goal. Suddenly, I have to really think about how I can pinpoint those states. What about the states that are exceeding expectations? What are those expectations? Which state has the most revenue? Which state has the least? So many questions that I have to think about and process data to get to my answer.

But if we visualize the data, I can find the answers and avoid an oncoming headache from the cognitive crunching I was doing on the data above.

Figure 1 shows the visual results of the same data. With a quick look, I can see that Minnesota, Illinois, Indiana, and Massachusetts all fall below the revenue goal. And, I can easily see the rest of states exceed them.

But, what about the highest revenue producing state? Am I able to determine that from my map? Suddenly, my brain kicks into gear and I start filtering the list above, only looking at the states that are in green, but I can’t identify exactly which state has the highest revenue.

However, I can change the way the data is displayed and ranked to see the highest revenue producing states down to the lowest. Using Figure 2, I could quickly determine that Tennessee is my highest revenue producing state year to date. Changing the visual representation of the data answers my question, but I’ve lost perspective on which states are exceeding or missing revenue expectations.

By adding color to my new chart, I can satisfy both requirements and quickly understand the data set. My brain doesn’t need to work so hard thanks to color-coded data visualization below. (Figure 3).

At this point, I might also consider adding the absolute revenue amount on my chart. However, when I do this, suddenly my chart becomes less usable because there is just too much information to try and digest. (Figure 4)

Just adding more elements for the sake of full disclosure, doesn’t guarantee an improved visual. Simplicity is the best approach.

Simplicity is the best approach. #dataviz Click To Tweet

So, whether you utilize the Gestalt Principles to affect your behavior with data visualization, or simply go with the ‘a picture is worth a thousand words’ saying, the end goal is the same – utilize data visualization to boost your brain power. It stimulates both the creative and logical side of the brain. Your brain will appreciate that you are feeding it information that it can immediately process and digest through the visual lens, rather than having to work hard for the same result. Who knew data could be so good for the brain?

Want to learn more about how you can take your data visualization from good to great? Check out our top 5 tips here.