Big Executive Data Dashboards

Hey Big Data, where are the dashboards your promised?  Where are the insights that jump off the page and scream insight?  How about just one clear presentation that leaves everyone going “Bingo” vs. “Yeah that is what I suspected.”  Oh, I see.  Big data is not built for that?

Big data can’t be something we slap onto any and all concepts and expect it to solve world hunger.  Big data is a big guess if we can’t put the insights into action.  Big Data is not a Guru that will speak wisdom when asked.

Companies have been evolving strategies for visualizing big data, while others slap the term on old technology.

“U.S. aerospace and defense contractor Lockheed Martin has partnered with Norwegian media technology developer Vizrt to create a big data visualization tool that combines real-time data processing and display with sensitive multi-touch hardware.”

Interesting pitch but missing the point.   If you read this sentence closely it suggests that combining real-time data with multi-touch hardware is the win.  Not so much.

There there is TQP.

 “TeamQualityPro is code agnostic and built on lean architecture. An organization can rapidly connect and define views and investigate teams and projects in each development phase from requirements through production.”

I like this PR web release a lot.  It’s what the company is pitching, and that’s not big data.  Again we see the real-time and project management themes pushed through the content.  Is big data only about real-time?  Enhanced project management so employees can make decisions in meetings? You would think so by the offerings and language used here.  This is ironic as big data would really be big consultant.  I can hear it now.  Staff:  “Big Data, speak to us about our project.”  Big Data:   “Ok. here are some data points, go forth and make decisions, let me know if you need more data.”

Then the venerable IBM.

 “IBM helped a major bank unify its credit risk exposure strategy for its wholesale lines of business with this new solution. Prior to deploying it, the management of credit risk was extremely difficult, often requiring four to five business days to aggregate more than 150 systems for a single entity. The complex process produced information and reporting challenges which comprised the accuracy of risk reporting.”

Big data is data aggregation for the sole intent of presenting unified data to reduce risk?    Missing the point again.  While there is no risk in hiring IBM, it would seem there is risk in waiting for real big data to come to market through them.

Maybe I am missing the point of big data.  Let’s look at what Wiki says:

“Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. …”

Yet,  It’s almost impossible to find a solid clear definition in market let alone having it slapped on to every old business model there is for added confusion.  Big Data is clearly the wrong term to use.  That is clearly a technology solution.  It’s that simple.  Thought leaders like Gary King say it this way:

 “There is a big data revolution,” says Weatherhead University Professor Gary King. But it is not the quantity of data that is revolutionary. “The big data revolution is that now we can do something with the data.”

So “Where’s the Beef”?  It’s in the reality of visualizing and digesting the big data into relevant and actionable tools.  Vastly more powerful models need to be explored while using big data for something other than it’s definition.  In fact, I advocate calling this science Information Diversity.  Diversity in acquisition, process and visualization.  The real failing of dashboards was assuming the output and forcing the input to match.  Dashboards that looked like car dashboards are just one of these crazy metaphors put into practice.  If big data was truly creating new and possibly spontaneous insights, a dynamic and responsive visualization tool would be the requirement.  Diversity display tools would be dynamic and interactive when information diversity did not match the display provided.

“Those who possess the skills to parse this ever-growing trove of information sense that they are making history in many realms of inquiry. “The data themselves, unless they are actionable, aren’t relevant or interesting,” is Nathan Eagle’s view. “What is interesting,” he says, “is what we can now do with them to make people’s lives better.””

Clearly we wan to make peoples lives better.  Maybe starting with the insights we can see will help.  Big data is dumb data if all we ask is what we expect.

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