BIG DATA VS. THICK DATA
Big data in contrary to as the name suggests, is not about the measure of data but rather “big” denotes being important. It is a means of collecting voluminous amount of structured, semi structured and unstructured data from conventional and advanced sources both inside and out of the organization, analyzing it by finding trends, abnormalities, or new structures and storing it, and converting all that data resource into something of significant worth. Big data is barging in from various sources at a tremendous velocity, volume and variety. It’s not just about data; it likewise incorporates the general population, procedures, and analysis by which we continue to discover the interaction of humankind with the world. It provides us valuable new insights for efficient decision making—enhancing operations, strengthening client relationship, counteracting threats and dangers, and increasing income. Study of big data sets can bring information like identifying trends in business, diseases avoidance, fighting crime etc. customer information from CRM systems, customer information from CRM systems, customer feedback streams, and social media platforms.
However, Big Data tends to put a significant value on quantitative outcomes, while diminishing the significance of qualitative outcomes.
Thick data leads to the idea that numbers alone are insignificant. Qualitative research methods are used to insights into the everyday lives of people in order to comprehend data in true terms. This provides inspiration and motivation to the company, something which the big data does not offer. The expression of gathering and analyzing information like trends for when targeted customers would certainly make a buy, and what are they presumably going to purchase, produces human behavior analysis. For e.g. Samsung conducted a research using thick data to gather information on what advanced design ideas customers want to see in their new TV product before its launch.
FROM ‘BIG’ TO ‘THICK’ AND ‘THIN’
However, a new approach is rising, named as ethnography: coordinating “thin” big data with thick data. Both big and thick data are important on the grounds that each of them produces diverse sorts of bits of knowledge at different levels. Big Data requires enormous sources to uncover patterns at an excessive scale while Thick Data makes use of little sources to discover human-focused patterns .At enterprise level, however, today the term big data is greatly considered. Since a long time, organizations have been making business decisions based on this big data, hence it holds greater importance in corporate world.