Yesterday’s Gala Dinner took place at the Museu Nacional d’Art de Catalunya (MNAC), a magnificient building overlooking the city and fine art from as early as the 11th century within its walls. After a day packed with announcements and thought-provoking keynotes, you might have thought that the relaxed atmosphere there would have been soothing. Nevertheless, I felt the need for a really quiet moment and sneaked away from the general excitement for a few minutes. And what I found was the exact antipode of what David McCandless had impressed us with during the day: ambiguity. Pieces of art don’t drive home a message but invite you to contemplate over, and possibly interpret them. It’s just surprising how refreshing this can be after an exciting and – in a positive way – also exhausting day.
This brings me to the point that I haven’t reported yet about yesterday’s media roundtable. Many journalists attended and David McCandless’ keynote on data visualization apparently touched his colleagues’ nerves. Being asked about the differences between traditional information graphics and his own ones, McCandless said he is aiming to remove as much irrelevant information as possible to get to the core of things, discover new correlations and challenge traditional views.
And that’s exactly where analytics for business intelligence purposes is heading today, said Teradata’s CTO Stephen Brobst: “Whereas traditional reporting tools were providing answers to pre-defined questions, todays analytical environments offer opportunities to think out of the box and help to find new questions to develop cutting edge business strategies.”
Oliver Ratzesberger of eBay agreed. His company leverages data visualizations to discover emerging trends on its virtual marketplace more easily. “We offer specific visualization classes for our data analysts. We really want them to play with data so that they may actually find new nuggets”, he said. As a pioneer of “sandboxing” virtual data marts in its EDW, eBay has the culture, the dedication and the infrastructure to develop and test new service products. To foster an innovative atmosphere, eBay is even hiring scientists that bring in a culture of experimenting with data.
Daniel Rodriguez Sierra from Telefonica was taking the same line. “Human beings are very good at recognizing patterns. The challenge is to display data in a way that it allows human beings to make full use of this natural strength.” He added that the data alongside with the analytic systems has actually become as important to his company as its physical network. Telefonica has chosen a group-wide approach to business intelligence, enabling all of its companies to use sophisticated churn prediction models. The company can also manage the entire network more intelligently and expand it in close alignment with the quickly changing customer behaviour.
So where are we going from here today? Pushing the limits of analytics further once again, we are going to learn that there is a case for data analysis in Formula One racing. If you think that it must be CRM, or at least nothing sports-related, then re-read Hermann Wimmer’s post about what it does for football.
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