Gartner’s Missing V’s: Value and Veracity

Much has been written about the three V’s of Big Data .  As a matter of fact Gartner claimed these V’s – volume, velocity and variety – over 11 years ago according to their Deja VVVu blog post earlier this year.  At Objectivity, we think Gartner was spot on with their revelation at the time… but things change.  Since we have been in the Big Data business for more than 22 years, we know that there are other businesses and players that have been conquering Big Data and now have evolved that landscape beyond simple management to real-time analysis of complex data as well.  Almost a decade later Gartner’s original set of V’s are missing what is being realized by companies today – Value and Veracity. In our DBTA webinar this January, Leon Guzenda, founder of Objectivity discusses the 5 V’s of Big Data in his presentation and recently IBM joined in on the discussion as well. Let’s start with Value: Yes, there is a lot of big data out there, e.g. the many types of logs (Splunk) from M2M systems, location data, photo/video data, etc. At Objectivity we believe that inside your data there are relationships, either explicitly or implicitly hidden within data. And in those relationships lies the true Value of your data. Examples include telephone call detail records (CDRs, from/to subscriber #), network logs (TCP/IP logs, source and destination IP addresses), and web logs (clickstream data). Extracting this set of columns data can build a very nice graph. The question then is how to utilize this information to get commercial value out of it. The point...

Big Data And The Trough of Disillusionment – Graph Databases to the Rescue

A few weeks ago the folks over here at Objectivity had a good laugh reading Arik Hesseldahl’s accurate portrayal of the Big Data craze in his article called Has Big Data Reached Its Moment of Disillusionment? In the article Hesseldahl turns to Gartner’s description of the hype cycle and the painful unfulfilled promises of Big Data technologies like Hadoop. The Hype Cycle goes like this: A new technology that promises to fundamentally “change everything” gets talked up incessantly in the press and at industry events and often also in research reports. At some point the chatter peaks, and expectations reach a fever pitch. Soon, maybe a year or two after it all started to build and some money has been spent and everything that was supposed to have changed for the better actually hasn’t, the narrative focus turns negative. What seemed so brilliant and earthshaking 18 months ago, seems in retrospect to have been an ill-advised waste of time, money and attention. Funny or not, we are sitting in the middle of the Hype Cycle as a market space; where companies are learning to manage Big Data but have no idea what to do with Big Data.  Hesseldahl points out that Gartner analyst Svetlana Sicular argues in a blog post that companies are struggling with a basic problem: What questions do you attempt to answer with your data in the first place? “Several days ago, a financial industry client told me that framing a right question to express a game-changing idea is extremely challenging,” Sicular wrote. “First, selecting a question from multiple candidates; second, breaking it down to many...