Data For All! How New Tools Democratize Visualization

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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