Please allow me a few questions before starting this post. Have you used a social network today, or have you purchased something over the Internet? Maybe you have used your credit card? It is highly probable that you have contributed to the billion daily Google searches, to the million Facebook updates or to the more than 10,000 credit card transactions that take place every second. All this creates an avatar of you with behavioural patterns and tendencies.
Today, the amount of information is still able to stress the capacities of computers, but an unstoppable race has begun which will change the rules of the game. Maybe the simplest way to understand the application of managing this colossal volume of data would be to mention an event featuring the Americana Target chain when it sent discount coupons for maternity and baby products to an adolescent. The girl’s father went to the chain to make a complaint but a few days later the truth came out: the girl was pregnant. How is it possible that this store was able to anticipate this and send coupons for products that this girl was going to need? It simply analysed her avatar… She had purchased vitamin supplements, perfume-free wipes and other types of products that led the shop’s software program to consider her a potential mother.
Our avatars grow over time, becoming increasingly complete, and we do our job of feeding them daily by using social networks or by purchasing a book on Amazon. In the United States, one in three newborn babies has an online presence since before birth (with their ultrasound pictures)… In a few years it will be very easy to know whether they play football on Sundays and that they might need a new pair of boots…
The question we now face is – what data should we explore?
Let’s see a classification of the information provided to us by these avatars:
- Big Transaction Data: This includes invoice records, in telecommunications detailed records of calls (CDR), etc.
- Web and Social Media: This includes information obtained from social networks such as Facebook, Twitter, LinkedIn, etc, blogs.
- Machine-to-Machine (M2M): M2M refers to technologies that enable connections between devices. M2M uses devices as sensors or gauges that capture a particular event (velocity, temperature, pressure, weather variables, chemical variables such as salinity, etc.).
- Biometrics: Biometric information such as fingerprints, retina scanning, facial recognition, genetics, etc.
- Human Generated: telephone calls, voice notes, email, electronic documents, medical records, etc.
We have already started to build the ecosystem of metaphysical resources necessary to analyse these large amounts of data, we have started the IKOR 4.0 project.
One last thought dear reader, both you and IKOR have just fed our respective avatars with this post.