When you buy through affiliate links in our content, we may earn a commission at no extra cost to you. Learn 
Using technology to assist in the process of acquiring, organizing and analyzing data in order to make better decisions is nothing new, but it does have a new name, and that name is big data. That name also gets a lot of hype. In this article, we separate the hype of the buzzword from the reality of the situation.
I talked to Gil Press, thought leader and managing partner at the marketing, publishing and research consultancy gPress. So let’s take a step back and look at why the big data buzzword has hit the mainstream, and what potential it holds for the future. (For some background reading, check out Big Data: How It’s Captured, Crunched and Used to Make Business Decisions.)
The Big Data Hype
Want to know the real reason the term big data has become so popular? Gil Press, a top thought leader in the field has some answers. Having held senior marketing and research management positions at NORC, DEC and EMC. More recently, he acted as the senior director of thought leadership marketing at EMC, where his studies "How Much Information?" (2000 and 2003 with UC Berkeley) and Digital Universe (2007-2011 with IDC) helped launch the conversation about big data.
"Big Data is one of those labels that emerge from time to time and has become popular as a catch-all phrase to describe a new set of technologies and processes and their potential or real impact on life and work, Press said.
"Typically, a technology-related term becomes popular, or becomes a buzzword, because a number of small and large technology vendors start promoting it heavily. Around 2005, Web-based companies such as Google, Facebook and Yahoo started to develop and deploy new tools designed specifically for the processing and analysis of large-scale collections of unstructured data.
"When these new tools and technologies were later developed further by start-ups – and when they were used by small companies selling data mining, business intelligence and analytics products and services – they all adopted big data as a way to differentiate themselves from competitors and disrupt the existing market," Press said.
So what was the final boost that made big data a top tech buzzword?
"It came from the big technology vendors who, in some cases, acquired these smaller companies, and put their large marketing budgets and market power behind the new term," according to Press.
As for big data analytics, that term found its roots in marketing, too.
"It is interesting to note that as a way to bridge between the most recent data analysis-related buzzword, "analytics" (popularized by Tom Davenport in 2006), and the new one, "big data," many IT companies have been promoting the combo "big data analytics," Press said.
Past the Hype: Big Data’s Benefits
Looking past the hype, Press explains that the drivers behind big data’s physical attributes can be attributed to:
- The increasing number of devices capturing and creating data
- The increasing interconnectedness of the data
- Inexpensive storage capacity
- Innovative software for processing and analyzing the information within the data
"For organizations, government agencies and individuals, big data means a new skill that could assist in making better decisions.
"Trying to make better decisions is not new, but the term "big data" points to a new mix of technologies, processes and practices that contribute to the development of a new competency in getting value from data, whether large or small," Press said.
When asked what big data will look like in 10 years’ time and whether it will be possible to get real-time analysis of all the world’s information, Press said he was hesitant to make predictions for the future, but does provide further insight into some reasonable assumptions.
"I think it is reasonable to assume that there will be more data and that we will have new tools for cleaning, processing and analyzing the data," he says. "More data will be used, for better or worse, to support decisions made by organizations, governments and individuals." (Read more about the growing pile of digital data in the infographics, How Much Data Is Generated Online Every Minute?)
Aside from being a powerful money-making, risk-reducing mechanism, the true value of big data lies in its ability to influence people’s lifestyles in a positive way. Mr Press provides comments on how some true value can be realized from the big data phenomenon – starting with health improvement.
"I’m not sure lives can be extended thanks to big data, but if this is possible or will be possible, then it will certainly make an impact on individuals," he states. "Staying in the health care field, but with somewhat less ambitious goals, big data may help us live healthier lives and improve our health-related decisions," Press said, citing new health care apps as a key tool in this area.
The First Law of Big Data
Finally, Press said that it’s not just up to scientists to improve and make use of big data – an average person can help as well.
"What I call the First Law of Big Data states that the value of data grows with the growth in the number of people sharing similar data – or in the phrasing of Metcalfe’s law, the value of data is proportional to the square of the number of people sharing similar data," Press said. "The more we share our personal data, the more value we – and the world – may get out of it."
A Big Data Experiment
Don’t just believe the hype, find out what the big data phenomenon means for you or your organization through this simple thought experiment: Identify a major problem or frustration in your life or work and ask yourself a question whether big data can play a part in the solution. (For more insight into how big data is changing, read The Evolution of Big Data.)
Check out the full interview with Gil Press below.
Troy Sadkowsky: What is your definition of big data?
Gil Press: Big data is one of these labels that emerge from time to time and become popular as a catch-all phrase to describe a new set of technologies and processes and their potential or real impact on life and work. For organizations, government agencies and individuals, big data means a new skill that could assist in making better decisions. Trying to make better decisions is not new. But the term big data points to a new mix of technologies, processes and practices that could contribute to the development of a new competency in getting value from data, whether large or small.
TS: What will big data look like in 10 years?
GP: In relation to the above definition, big data is impacting the amount of data, the speed at which meaning can be inferred, and the speed in which an action be taken. Will it be possible to get real-time analysis of all the world’s information on any curiosity?
I’m hesitant to say anything about the future. But I think it is reasonable to assume that there will be more data, that we will have new tools for cleaning, processing and analyzing that data, and that more data will be used, for better or worse, to support decisions made by organizations, governments, and individuals.
TS: Are we going to hit a quantitative upper limit in the above attributes? Moore’s law is holding true now for transistors, hard disk storage, network capacity and pixels, but how long do you think it will last?
GP: Moore’s law will last as long as human ingenuity will last. It has served as a motivational goal for engineers and for more than four decades they have found ways to overcome any perceived limitations.
TS: Why has big data become so popular recently?
GP: Typically, a technology-related term becomes popular, i.e., it becomes a buzzword, because a number of small and large technology vendors start to promote it heavily. The term "big data" was used in the context of data visualization applications for science in the late 1990s. Around 2005, Web-based companies such as Google, Facebook and Yahoo started to develop and deploy new tools designed specifically for the processing and analysis of large-scale collections of unstructured data. When these new tools and technologies were later developed further by start-ups, and when they were used by small companies selling data mining, business intelligence and analytics products and services, they all adopted big data as a way to differentiate themselves from competitors and "disrupt" the existing market. The final boost that made big data a buzzword came from the big technology vendors who, in some cases, acquired these smaller companies, and put their large marketing budgets and market power behind the new term.
It is interesting to note that as a way to bridge between the most recent data analysis-related buzzword, "analytics" (popularized by Tom Davenport in 2006), and the new one, "big data," many IT companies have been promoting the combo "big data analytics."
TS: What is the true value in big data? Money can be made, lives can be extended, risks can be reduced and prestige can be achieved, but what can big data do for the average person?
GP: I’m not sure lives can be extended thanks to big data, but if this is possible, or will be possible, then that will certainly make an impact on individuals. Staying in the health care field – but with somewhat less ambitious goals – big data may help us live healthier lives and improve our health-related decisions. This is apparent in the burgeoning field of "personal analytics," starting in 2006 with the Nike+ shoe connecting to the iPod.
Today, these apps are moving from monitoring and analyzing your exercise routine to assisting with your health, wealth and work. I believe that we will see these apps move further into what I would call "personal big data," allowing you to compare yourself to others, providing individuals with tools for analysis of the relevant large-scale data.
TS: What action should the average person take when it comes to big data? Is there something that we can all do to help?
GP: What I call the First Law of Big Data states that the value of data grows with the growth in the number of people sharing similar data. Or in the phrasing of Metcalfe’s law, the value of data is proportional to the square of the number of people sharing similar data. The more we share our personal data, the more value we – and the world – may get out of it.
Thanks to Gil Press for the interview. You can check him out – along with a long list of other big data experts – in Big Data: Experts to Follow on Twitter.
