TECH | Aug 17, 2017

Name of the medicine: Big Data

If Big Data were a medicine: read the instructions and warnings for use very carefully


Big Data, according to the Treccani dictionary, is “a huge set of digital data that can be quickly processed by centralised databases”. According to the Cambridge Dictionary, however, it is “very large sets of data that are produced by people using the internet and that can only be stored, understood and used with the help of special tools and methods.”. According to Wikipedia it is “a term used to describe a collection of heterogeneous, structured and unstructured data, defined in terms of volume, speed, variety, and truthfulness.” Other “Vs” are added to the essentials in other definitions (from Variability to Veracity, Visualisation to Value to … ‘Whatever’).

The heterogeneity of the definitions and the inaccuracy that excels in official sources (Treccani: centralised databases? Who said! Cambridge Dictionary: produced by people? And the Internet of Things?), highlights an interpretative complexity that sometimes (indeed too often) sees the concept of Big Data being stretched to fit the purpose.

In general, the concept expresses the complexity of a world that produces a large amount of particularly heterogeneous data that changes with great speed and has to be interpreted according to analytic techniques (big data analytics) based on the extrapolation of non-linear inferences between the analysed data. Often (again all too often), those discussing Big Data refer to Big Data Analytics.


Big Data can be used in all those conditions where it is important to highlight non-linear correlations between data and information. From marketing to medicine, from politics to meteorology, traffic flows in urban contexts to the risk index for life insurance. It is used to highlight links between seemingly unrelated data, to identify trends and intercept patterns.


The term Big Data should not be used in reference to instruments of the size and complexity of your telephone’s index, with the numbers of your friends and relatives. Generally, it should not be used every time you refer to data that has no relation to the term “big” in terms of volume, variety, speed, and/ or a chosen “V” set cited in the “What is it” paragraph of this leaflet.
It is advisable not to use Big Data and the analysis techniques based on it if you do not want to get unexpected results, or when you do not need – or have the courage – to look at the reality from an interpretative perspective rather than an ordinary one, or when you do not really want to identify inferences that may alter your plans.


The effect of the medicine can be altered, reducing its effectiveness or nullifying it altogether, if used without the necessary precautions. Specifically if taken without regard to the type and quality of the data to be considered and the procedures that will guarantee its availability over time. The effect can also be changed if taken irregularly, without a structured and organic care plan.


How much

Big Data can be taken in large quantities as long as the specific typology of the active ingredient is kept in mind. It is not harmful to health, except in the cases described under “Precautions for Use” and “Undesirable Effects”.

When and for how long

Big Data can be taken regularly, even in small doses for a long time. It is not addictive. The benefits of reading and analysing data may in some cases be immediate, in others – depending on the physiology of those taking it – may take longer to be accepted. In some cases, in fact, taking Big Data generates immediate effects because of the option to look at phenomena that are thought to be understood, from different angles. In other cases, the capacity to look differently at facts and phenomena that are considered as already consolidated might take some time, also due to having to counteract the placebo effect resulting from established readings.


Big Data can be taken at any time of day, week, month or year. It is ideal if taken using a holistic approach, so that each action (found in the data it produces) impacts on the others and reading the data produced reveals the best way to act, according to the principle for which the physiological functions involved are intercorrelated.


In the event of Big Data overdose, you risk losing sight of the active ingredient’s starting point: analysis techniques based on Big Data favour the identification of “what happens” rather than “why it happens”. This can generate hallucinatory effects which may convince you that it is sufficient to analyse the “thing” rather than understanding the “why”. In such cases, it is advisable to offset the use of big data with increasing doses of business intelligence.


Gastritis, irritability, intense stomach acid, abdominal pain in individuals susceptible to the emergence of unexpected interpretations for the information available. In rare cases hallucinatory effects due to the need to explain evidence that emerges and for which you do not have enough time, capacity or desire to question why.

Sonia Montegiove – Stefano Epifani