Interesting series of conversations over the past few days was followed by the serendipitous New York Times article “A Makeover for Maps” by Quentin Hardy.
Data visualization is a daily part of my life as it can help alleviate the disruptive disorder known as analysis paralysis on its best days, on its average make a bunch of seemingly non-nonsensical spreadsheets legible and at its worst just make useless info look pretty.
Facts are meaningless. You could use facts to prove anything that’s even remotely true – Homer Simpson
There’s no replacing the classics in the art of data representation, charts and graphs, but new generation of data presentation architecture and interpretations are consistently emerging and it has me intrigued, not just how I can use it in my daily work life as a product manager but as the article alluded to how it can possibly change how we consume basic information as consumers.
Comparative information is longer completely static in nature. Maps, for example, already available in ‘real time’ displaying their initial cartography overlaid with data points about usage like vehicular traffic patters, mass transit arrivals or food traffic heading into the local McD’s. These are still though entry level concepts with pervasive acceptance and only begin to the power of such informational intersections.
At this point the limitation is two fold in the availability of data and the perceived usefulness of its display. However, as more data points are collected and properly aggregated (which is an inevitability) the real challenge will continue to be deciding how to combine the information into useful consumables.
If you are the NSA or big retail there’s probably multitudes of data intersections to be visualized offering insights into people’s every movement but not ever visualization need not seem so invasive. You’re probably using psychology, the library sciences, graphic design, analysts, database administrators and limitless unpaid interns to parse and present anything and everything you can envision even if it’s not even necessarily useful. The team it takes to bring together aggregate data in this volume extends well beyond marketing ‘experts’ playing in excel and power point, even if there’s a bit of an evil genius presence to some of alliances coming together to do it.
There’s an art as much as a science to selecting and graphically depicting the relationships between data points which I believe will be one of the next major leaps made in how humans interact with technology. It will go beyond just breaking your credit card purchases into simple pie charts to show you monthly spending or showing what your Social Network’s recent purchases by proximity and pricing where based on your relative interest for everyday users just like it will go beyond heat maps of user inputs for mobile product managers.
The result could be greater accountability by everyone in data interpretation for decision making. Rather than a small number of people with access to information for which they interpret and respond to providing direction to the masses, the vast amounts of data can be distilled for the use of many to create their own direction from. The vanishing consultant in theory becomes a problem of the past (although, perhaps not, since the initial visualization and the subsequent interpretation of the visualization could still require the influence of expertise that is lost over time).
The downside, of course, could be the misinterpretation of the data at any point in the process, such as extraneous causation and causality arguments in creating the visualization or interpreting the graphical result, otherwise known as truthiness. The greater ease in the manipulation of data the more potential there is for its misuse and abuse.
Extraneous uses not withstanding, the groundwork for adoption is already laid. For example, GUI (graphical user interfaces) once took complex computer programming languages and simplified them into icons and images that produce the same results to the point where the average computer user knows little, if any of the underlying information involved in the process as they have reached proliferation in every way we interact with computers.
Advanced data visualization can eventually produce the same expectation where users are not privy or even concerned to the underlying information but are interacting solely with the images produced depicting it. They can take for granted the underlying assumptions and react to and more importantly interact with the display itself rather than having to “run the numbers” as they might have to do now dealing with large data sets semi-manually. Infographic and visualization design is very much a subjective experience, and tools won’t ever replace careful, thoughtful data interpretation, however it’s equally important to remember data in-and-of itself no matter how well visualized still falls within interpretive measures that even the best conceived algorithms alone won’t replace.
Thus, the future of data visualization won’t replace what many of us do now manipulating information but it will be yet another asset we will (probably) take for granted in our interpretative process which is what the recent conversations has me most excited about as a start to the year.