Over recent years, major brands, companies, and even state agencies have dedicated a great deal of resources to the acquisition, analysis, and systematic interpretation of so-called ‘Big Data’.  Essentially, Big Data implies large volumes of numerical data that correspond to variables such as habits, preferences, interactions, and geographies of specific populations and groups of users or customers.

It is, therefore, easy to understand the value of such data for agencies of which success depends on decoding and staying steps ahead of the market.  Big Data may, for instance, be used to reveal which websites – or even more specifically which sections of those websites – are most popular with segments of consumers.  In one of its more complex uses, Big Data can also be interpreted and used to tentatively formulate which products a customer is more likely to buy or be interested in from his or her past purchases.

One of the most significant advantages of Big Data is that it may effectively reveal such general trends, as these present across large numbers of people.  Moreover, the collection, analysis, and interpretation of Big Data is also often done computationally through the application of algorithms, and the subjectivities (but also intuitions and connections) of a human researcher are thus altogether omitted from the research process.

There can be no doubt, therefore, that Big Data can offer valuable insights and information into past, present, and possibly even future consumer behaviour patterns.  As recently and validly suggested by the business anthropologists at the Antropologia 2.0[1] research agency in Valencia (Spain), however, the Big Data model also presents a series of limitations and shortcomings that require mitigation through other – largely non-computational but instead eminently ‘human’ – methodologies.  This is where ‘Thick Data’ comes into the play.

In this series, we explore the value and implications of ‘Thick Data’, as we delve into questions such as:

What is ‘Thick Data’?

What does ‘Thick Data’ tell us?

How may ‘Thick Data’ complement ‘Big Data’?

How is ‘Thick Data’ collected?

With particular reference to the Maltese context, how may ‘Thick Data’ may be used to reveal nuanced and complex dimensions of certain issues?

[1] Source: https://blog.antropologia2-0.com/en/what-is-thick-data/