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Given the entire buzz around big data technology, we decided to get some expert thoughts. And who else to ask than the father of data warehousing himself. In an exclusive interview with Analytics India Magazine, Bill Inmon shed light on his thoughts around big data. His suggestion: be cautious and focus on business value.
Analytics India Magazine: Given how Big Data is creating the entire buzz around it, as a pioneer in data warehousing, what are your thoughts about it?
Bill Inmon: The history of the technology industry is to oversell a new concept. That is why we have the famous Gartner hype-curve. I think there is no doubt that there is a legitimate marketplace for Big Data. But I think Big Data has been terribly overhyped. As witness to the overhype in the market place, take a look at the use cases that are presented as the end result of Big Data analysis. The proponents of Big Data are really struggling to justify the investment made in Big Data.
It reminds me of the hype that once (not so long ago) surrounded the Dotcom phenomenon. One day every corporation was doing Dotcom then the next day people realized that Dotcom was not nearly what was promised. While there were a few companies that came out of the Dotcom era as winners, the vast majority of the startups that came with Dotcom are nowhere to be found today.
The people espousing Dotcom failed to ask one fundamental question at the beginning. That question was – “what is the business value of Dotcom?’. The people going crazy over Big Data are making the same mistake. They are not asking at the outset – “what is the business value of Big Data?” So history is repeating itself and Big Data is destined to have the same fate as Dotcom.
AIM: Do you think the buzz would continue?
BI: The buzz is so strong that its sheer momentum will cause a continuation. However there will come a day for every corporation to ask the question – “have I gotten my money’s worth out of Big Data?” When that day arises the very strong momentum for Big Data will cease to exist. Undoubtedly there will be a few winners. But the reality will be far short of the promise.
The biggest factor in the progression of Big Data is not the vendors. It is the technicians who see Big Data as a way to get larger salaries. In addition the focus on Big Data allows the technician to get management to take their eyes off of the mess that most technicians have created with regular, non Big Data data.
AIM: What are the most significant challenges you face being in the forefront of this space?
BI: Over and over I tell people – do not invest heavily in Big Data until you can answer the question – “what is the business value of doing a Big Data project?” And over and over the vendor tells the corporation – just invest in Big Data and you will discover wonderful things that will make the experience worthwhile. And corporations just go on building Big Data projects hoping that the vendor is correct. And after a large investment has been made, there usually is some small result that surfaces that is worth a fraction of the money that has been spent.
It reminds me of lemmings. IT management around the world is acting like a bunch of lemmings, just lining up on the cliffs edge and waiting to anxiously hurl themselves on the watery rocks a thousand feet below. And while they are falling to their death, they are still congratulating themselves on how clever they have been.
AIM: What would be your advice for someone who would what to create a career in Big Data?
BI: The advice I have for everyone – neophytes and experienced people alike is – focus everyday on the business value you are providing. Do not get caught up in the intricacies of the technology itself. The real payoff (and the long term career) is in being able to extract business value out of Big Data.
AIM: How do you see BIG DATA evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
BI: While all the conversation is on Big Data (because vendors want to sell their products), there is a very real business oriented trend towards extracting business value out of textual information. The corporation is FULL of textual data that is not being used today for any kind of meaningful analysis. There are call center conversations, where the corporation can hear the voice of the customer. There are corporate contracts where corporate obligations such as corporate liability reside. There are emails where there is a wealth of information. There are medical records where trends in disease and outcomes are going unnoticed, and so forth. In short there is a wealth of textual information that is just sitting there waiting to be used in the corporate decision making process.
Ironically there is GREAT business value hidden in textual information where there is little or unproven business value in Big Data.
And a few organizations are starting to look at text and are starting to find big payoffs there.
By the way there is a very real difference between text and Big Data. Much text never is written on Big Data and much data in Big Data is decidedly non textual. There are some people that say that text and Big Data are the same thing. They are not.
AIM: According to you, which are some of the interesting players/ companies in Big Data space currently?
BI: There are many companies in the Big Data space – some of them established, some of them brand new. There are IBM and Teradata and HP. There are Cloudera and HortonWorks.
Big Data is the same way. If you understand that you MUST first and always get business value out of Big Data then use Big Data to get that value, then the mustang (and Big Data) becomes a valuable and long term asset. But if you do not approach Big Data this way, then be prepared to be kicked and thrown to the ground in a most violent manner.
There is great opportunity associated with Big Data, but only if you approach Bug Data in the right manner.
AIM: Anything else you wish to add?
BI: Whatever you do, understand and focus on business value at all times. Do not get distracted by the technology associated with Big Data. Look at Big Data as a tool to get you where you want to go, not as an end unto itself.
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