Recently, we’ve written about how just changing the way you look at a problem can offer new insights into its solution. Not only that, but looking at problems in a new way can actually lead you to faster, more accurate decisions than slogging through mountains of information and trying to solve the problem in the traditional, more analytic method.

That whitepaper got us thinking about the best data visualization tools available today, and what exactly goes into them. As we were doing some research we discovered that all of the best data visualizations and tools to create them had a few common aspects to them.

So think of this as a checklist with examples- run down this list before you make any software purchases to ensure that you’re getting the best tool out there to help you be more efficient and have even provided examples to show you what we mean.


The first function of any good data visualization is usually the first thing you think of: it should aggregate data into one system for easy analysis.

But let’s unpack that statement a bit shall we, because if you think more closely about it aggregating data is actually a larger task than you might think. What we are talking about here is breaking down data silos, gathering data from various databases, spreadsheets and other sources and putting them all into one program for visualization.

Some people call this step in the process data massage or data plumbing. We just call it breaking down barriers and gathering all the information required.

EXAMPLES: Tableau, Domo


Once you’ve determined that your tool can gather all of your data into one place, you can start to decide what kind of visualization you should apply to it.

This is arguably the most important part of the process because not all visualizations are created equal. In fact, when most data visualization tools aggregate data for a visualization they put it all into a simple bar graph, pie chart, scatterplot or other diagram.

While these visualization methods have been adequate for over 200 years, there are other ways to visualize modern big data. Specifically, you should look for a visualization that not only aggregates data and gives you a big picture overview, but also one that allows you to drill down to the actionable details that make up the bigger picture- those are where you can make the most efficient changes to improve efficiency.

EXAMPLES:, EveryNoiseAtOnce


Data visualization should not be the same for everyone. The information that CEOs and entry level employees need are drastically different from one another- one graph is just not adequate. Luckily, most modern data visualization tools offer the ability to generate customized reports and visualizations that are tailored to the specific business user’s needs.

But this is just the beginning. If, in fact, looking at a problem in a new way is the key to making faster, better decisions then the ability to manipulate live data inside the visualization to create a custom view should be quick, easy and intuitive.

The ability to create custom visualizations in real time is a relatively new development, but we are firm believers that it’s the future of big data analytics. The ability for anyone, regardless of training, to create custom visualizations to find answers to their problems is data democratization at its finest.

EXAMPLES: Cinemetrics, OneMillionTweetMap


This is something we care deeply about, and it’s actually one of the rarest aspects to find in any modern data visualization tool: transparency.

We aren’t talking about transparency in the sense that all of the information is available in one spot: we’ve already covered that when we talked about data aggregation. No, we’re talking about how the data is visualized once it’s aggregated. Spreadsheets are the most obfuscating: it takes even a data expert a long time to get any sort of valuable information from them. Traditional visualization methods like bar charts aren’t much better: they present the information visually, but they lose the important details in the data. The same details that would allow someone to know exactly what they should be working on to improve.

But here’s the catch: visual representations of data that include both the high-level, strategic thinking of a bar chart while keeping the actionable details intact are rare enough, let alone a tool that presents them in a way someone can understand.

Luckily this is a burgeoning field of data visualization research and multiple experiments have already been conducted that show the power of such systems. Visualizations that combine big-picture thinking with detailed information are at the heart of transparency: a visualization anyone would be happy to explore!

EXAMPLES: VisualCue, climatecentral

Until next time,

The VisualCrew