According to latest Cisco reports, global internet traffic will quadruple from 2010 to 2015, reaching 966 Exabytes (EB) per year.
Just to keep things in perspective:
1 EB = 1 000 000 terabytes = 1 000 000 000 gigabytes.
Looking a bit backwards, according to an estimation from Eric Schmidt, former Google CEO, the total of human knowledge created from the dawn of man and digitized till 2003 totaled 5 Exabytes.
These two values are so far apart in scale, dimension and time, that the logical conclusion should be that our ability to create data completely overpasses our ability to digest it. At least, that was the general consensus on the matter. Until now.
Journalist James Bamford has confirmed in a recent Wired cover story older rumors that USA’s NSA is finalizing as we speak a massive surveillance center in Utah which will be able to store and process Yottabytes of data (the biggest data measurement unit yet). (1 million Exabytes = 1 Yottabyte).
In short, this is the big data that transpired about the Utah Data Center:
It will cost roughly $2 billion dollars and it will be finished sometime late 2013.
It will store, monitor and analyze virtually all communication channels (internet, mobile phones, etc).
It will be used to try and crack the AES encryption, the cryptographic standard considered unbreakable so far “in any amount of time relevant to mortals”.
This means you needn’t worry, the Jack Bauers of the online are hard at work in dealing with Big Data issues…
In fact, Big Data’s definition a while back was “data that exceeds the processing capacity of conventional data systems”. Big Data has two dimensions, one bigger and more complicated than the other: data collection and data mining. If data collection is one of those expressions that explain themselves, the concept of data mining might be a bit harder to understand. Basically, data mining is used to simplify the collected data in a way that analyzers will be able to understand it. Data mining, for example, can put your life together from small bits of information. One check-in here, one status up-date there are not important in themselves, but coupled with the book you bought and the restaurant where you eat every week can go a long way in painting a fairly accurate picture of your profile.
Data mining, in fact, is all about pattern detection.
And pattern detection leads further to predictive behavior.
Predictive behavior is, in fact, what data mining is all about. So far, all this meant, of course, that the only ones who could even dream of taming thins kind of vast amounts of data were the Googles and Facebooks of the planet. Facebook can predict you want to buy a Nissan GTR because you uploaded pictures of it constantly for the past year and you’ve also chatted about it several times. It can also serve you ads of Porsche, while we’re at it. And the same way, Amazon can predict you will buy The Bourne Legacy, because you already bought the first three ones the second they were released. Well, big date processing is no longer restricted to the giants.
After much experimentation and exploration, the emergence of Big Data into the enterprise can turn smaller companies from subjects to users in a way that can benefit all parties involved, for a change.
In CRM, for example, the move towards the cloud and sales process implementation were huge steps in increasing productivity for companies. However, the CRM potential is still huge and by all accounts it will rocket with the full potential behind the game changing concept that combines Big Data, Personal Networking and Sales Integration into CRM.
The moment when companies will use the overall personal network of all employees in order to find contacts at potential clients suggested by Predictive CRM solutions based on Twin Client Analysis (industry type, turnover, number of employees, location, etc) is not far.
And now, for a bit of shameless promotion, we’re happy to say we’re the first ones implementing all this in our application.
What do you feel about Big Data and CRM?