armando_alvarezBy Armando Alvarez
Innovation Leader  
[email protected]




Beyond the momentum of the new high-performance technologies to store or process large volumes of information, as well as advanced analytical techniques, which allow the exploiting of data to predict or optimize future scenarios, the concept of Big Data can mean paradigm shift in how to deal with decision-making, not only in business but in everyday life.

However, this possibility depends on the existence of questions that allow the use of “Big Data” to really  impact the results of the decisions made.

To quote an example; You may have multiple measurements per minute on hundreds of indicators to monitor most of the biochemical processes of the human body from nanotechnology. Imagine also that we have stored historical information for the entire population and have related to their individual medical record.

So it’s not hard to imagine that it is possible, from basic algorithms correlation between these indicators and disease events in the past, know when someone is going to suffer a disease at the time it begins to manifest at a biochemically level in real time.

“Big Data is the transformation of your information in an asset that generates competitive advantages”

This could mean the “cure”, or at least early detection of diseases such as cancer. This is exactly what we mean when we say that Big Data tools can mean a paradigm shift in how decisions are made to improve outcomes using data and technology. While this example may seem distant today there are multiple decision-making processes in which this model is already a reality:

  • Language translators from the use of millions of translated texts
  • Predictive maintenance of equipment from sensors data
  • Recommendation engines based on behavioral patterns of hundreds of thousands of users and products
  • Facial recognition from databases of millions of people

To materialize these efforts, as mentioned, first it is require good questions (use cases).  Technological tools and the mathematical models such as the one  TARGET used to know when a couple will get pregnant before they do,  are based on their buying behavior, but the important question was:  How I can know that a couple will have a son to profile it and propose an offer of value that makes them my loyal customer? In Intellego Group we know that there is a very large to change the way how our customers may face strategic decisions, based on the possibilities of analysis of large volumes of information opportunity.