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The data revolution – whether you are ready for it or not – has already arrived.  Excel spreadsheets have been kicked to the curb, and there are several new data sheriffs in town.  Data visualization, analytics, and other big data technologies have replaced our old ways of synthesizing business information.  And not only is it different – it comes in mass quantities.

Functioning under the term “big data,” companies and analysts alike realize there is a lot of it, but as they sift through the immense swamp of data, they often struggle with its general application, and even its importance.  During Data Innovation Day on Jan. 22, data scientists, technologists, and other experts discussed exactly why such innovation matters.

The Center for Data Innovation brought together Mark Silverman, CEO of Treeminer; Gerard Valerio, DATAvangelist at Tableau, Chris Surdak, Author of Data Crush; Michael Wilde, Chief of Awesome at Splunk; Sridhar Iyengar, Distinguished Engineer at IBM Research; and Angel Pizarro, Technical Business Development Manager of Amazon Web Services, to discuss Innovations in Analytics, Visualization, and Big Data Technologies.

Each panelist began with their take on the biggest data change they’ve seen and how it has impacted their business world.

Wilde kicked off the discussion with an example of a Japanese company in Japan that owns office buildings.  By collecting data on human behavior from their machines such as building elevators and card swipes, they were able predict future economic activity, such as whether or not a tenant might decide to renew their lease.

Other panelists had similar stories within the predictive data scope, but ultimately the predominant change, and also the challenge, remains in the variance of structured and unstructured data.  Sridhar Iyengar of IBM said that while we now have more data varieties, how to sift through it is anybody’s game.

“We now have access to X-Rays, tweets, emails, and Google Hangout Video – but being able to get useful info and insights from this data is a huge problem because there is no way to search it,” he said.  And without search, panelists agreed, businesses are not able to obtain anything that didn’t already know.

“No point in knowing what my customer does second by second, if it takes me an hour to find it,” said Chris Surdak.

How exactly do companies begin to gain any value out of this data?

Surdak called it “action at the speed of insight.” Right now companies rely too much on the customer data “swamp,” he explained, but the real change should come from within first. Companies have to fix their internal operations first, or they are will be, as Surdak put it, “hosed.”

In addition to revamping your business operations, creating new business roles might be necessary.  Iyengar foresees the role of data curator coming into play.  This person would not only mine the data, but work to clean up what is provided – both structured and unstructured data – ensuring it is both valuable and legitimate.

Wilde attested to the success that companies can achieve when they decide to take the data plunge.  One of Splunk’s clients, New York AirBrake, was able to save billions of company dollars based on machine data acquired from the operation of their brakes.  They found that if a train braked prematurely, billions of dollars were lost in fuel alone. This data allowed the team to better coach and train the operators, leading to better business decisions.

Mixing large datasets into the marketing mix requires specific plans and tools to break down a vast amount of information and find the core patterns and trends. These allow marketers to shape campaigns and place the right material in front of the appropriate audience at just the right time. Using big data to increase relevance will likely fortify a brand, and in return, lead to loyalty, consumer engagement, and retention.

“Data matters,” said Surdak. “Without data, everything else is just your opinion.”

Explore more data-driven issues and gain new, actionable insights and skills at the Email Evolution Conference 2015, February 2-4, the Marketing Analytics Conference, (MAC), March 9, and Mobile Marketing Day, March 12.