Author: Bill Franks

When I talk to organizations about how they are using data visualization tools I am often struck by the fact that they use these tools mostly to generate charts and graphs that really aren’t all that different from what they could have created with standard business intelligence or desktop tools. However, people get very excited about their output nonetheless. At first this surprised me, but then I realized what was going on.

I would like to suggest that data visualization tools such as Tableau and Spotfire, to name just a couple, offer two great value propositions — which are often intertwined into a single value proposition. Understand these differences and you’ll create more value for your organization.

The first value proposition is the obvious one, which is enabling users to create better visuals that bring their data and their analysis to life. This is the value proposition that most people focus upon and that gets the most attention. It is also the primary reason organizations invest in visualization tools.

The second value proposition, which is often either overlooked or vastly under-credited, is that visualization tools democratize big data by giving users wide flexibility to analyze data within a self-service business intelligence environment. Visualization tools allow users to explore, summarize, and visualize data in the way they see fit as opposed to the way someone else saw fit to allow them. By having the flexibility to join different data sources as desired, view patterns on the fly, and iterate, users can discover important insights and trends more easily and more rapidly.

Users may be able to access massive data sources in traditional environments, but they can only do so via predefined paths. On the other hand, common desktop tools such as PowerPoint or Excel that enable charting and graphing either require data extracts, which must be small, or more complex configurations than many are comfortable with. They are too complex and the visuals they generate aren’t very robust or interactive.

While many users of the new visualization tools spend most of their time generating basic output, they get really excited about their new-found freedom to navigate the data and view it from any angle desired. While the graphics generated may be simple, users are much more confident that they contain the right content.

The implication is that many organizations may not be getting the full benefit of their big data and visualization investments. But it’d be a mistake to make those tools available only to those users with advanced data skills. Using the tools should help even non-numerate users gain greater comfort with the data (one hopes) and along with that comes growing ability to draw increasingly sophisticated insights. And that’s when the big data investments really start to pay off.

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Our brains are meant to see in pictures. Grids and columns of data, while ubiquitous, make it very difficult to see trends or patterns. Additionally, a lot of the new data sources available today, such as genetic data or social network data, don’t lend themselves to traditional spreadsheets and graphs. These data types require a different way of displaying them to allow us to see the underlying patterns and stories in the data.

I’d like to walk you through an exercise to illustrate how effective visualizations allow you to immediately comprehend a complex set of relationships. Consider a standard map, such as the map of the United States below. If I show you the map and ask you to describe how a few states are related to one another, you can immediately visualize and verbalize an answer. New York is up and to the right of Virginia while Texas is down and to the left. There are several states in between the two and Texas borders fewer states than Virginia does. Simple, right?

Next, I take away the map and give you a set of data that gives relative location, size, spatial border details, and other information about the states. Could you describe the same relationships in just a few seconds based on the data alone? I’ll bet you’d throw your hands up in the air — just like me. I have never been able to find a remotely reasonable way to explain the information immediately visible to me in a map without making use of a map.

You might not immediately grasp the importance of the above example because it seems self-evident that maps are important. I’d like to suggest to you that the reason for that is that you are aware that maps exist in the first place. Had you never seen a map, you’d be struggling to explain the information that a map conveys in some other way.

This is the key to the value proposition of data visualization. It could be that you are struggling to convey information without being aware that there is a visual that can have the same type of impact as a map. Or there may be connections among all that data that you’d never make without a visualization. Until you see the visual for the first time, however, you won’t appreciate the value it offers. Take a look at the social network graph below: it shows is that there are several distinct groups of people who interact a lot among their own group and they don’t really interact outside of their group. However, there is a single person who has contact with each group and connects them. That person would be the critical one to reach if you want to influence those groups easily. See how easy it is to understand the connections between people and groups?

As the map example illustrates, data visualizations can make it easy to rapidly understand relationships, patterns, and stories that are contained within a complex data set. This is the reason they are so powerful. There is a reason for the saying “a picture is worth 1000 words.” It also holds for data points.

One of the best features of modern visualization tools is that they permit interactivity with the underlying data. In other words, a visual isn’t static. You can click on various parts of a visual to drill into different views of your data on the fly. While many business intelligence tools have enabled drill down reports for years, they typically contain only common visuals and also typically constrain users to predetermined paths. Visualization tools today don’t apply many limits on what users can do, which opens up a lot more options for analyzing data.

A few years ago, we put a popular visualization tool on my team’s laptops. It was a huge hit. Over time, several members of my team stopped using traditional spreadsheet and presentation tools altogether in favor of the visualization tool. Even if all they need to show a client are some fairly standard bar and pie charts, the interactivity of the tool is a huge plus. When the chart is up on the screen and a client asks a question that requires a different view of the data, it is easy to drill into that view on the fly. No more sending an email later in the day with another chart. The data in the charts can also be automatically updated with the latest data. That adds a lot of value on top of the visualizations themselves.

Don’t underestimate how much an appropriate visual can help you get your point across. You have to see the power of high-impact visualizations in order to fully grasp what is possible. The good news is that modern visualization tools can help users at any skill level do a better job of analyzing, comprehending, and presenting information. Give it a shot.

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