The term Big Data, and all associated statements, is a mere proposition.
What exactly is Big Data?
When the experts reference Big Data, they are dangling the carrot of improved business return from an existing resource. They are constructing a value added proposition.
A proposition is an evaluative judgement, not scientific theory waiting to be proved or disproved.
There is an important distinction between the two.
Behind every proposition lies self interest and generalisation.
Next time you read an article pushing Big Data as the answer to improving return on investment, take a look at the background of the author. Look for convenient, conditional truths. Identify where claims, beliefs and value statements have been created by the author, and then justified.
Sure, specific projects can bring additional return on investment, but this cannot be taken for granted from the generalisation that is big data, which runs the risk of becoming meaningless by the generation of knowledge for the sake of knowledge. In this case, big data can simply equal less and less meaning.
In comparison, scientific theory provides an objective view, to be tested until destruction, proved or disproved, until scientific theory moves on, yet again.
Making predictions of future behaviour on the basis of past and current behaviour is not valid.
Understanding people and their motivations can never be a science. Scientific theory aims for a generality that eludes the understanding of people. Understanding human behaviour means to know that they mean what they say, to determine intent, to know why actions are determined and what the value of repetition is.
Big data can undoubtedly play a role in getting towards solutions based on evaluative judgements, but it is not a scientific panacea. In marketing and advertising, science has no role for providing fail safe solutions in the world of semantics, perception and created realties.