A simple and concise model for defining new data generated by the increase in information sources and, more generally, by the evolution of technologies.
Table of Contents
Big Data is defined as data that has at least one of the following characteristics:
In the early 2000s, Big Data was defined with three words: volume, speed, and variety. Over the years, as the term lost its sci-fi aura to become increasingly concrete and applicable in companies, we wondered if there were other characteristics to highlight. Two new Vs. have enriched the model, aimed at defining how this new data should be used:
In recent years, Big Data has been defined as the new oil or gold, i.e., an invaluable source of value. That’s exactly how it is. But simply collecting data while exploiting the best technologies available on the market does not guarantee having information and, above all, extracting knowledge.
Talking about data, information, and knowledge means talking about related but different aspects. Data is a codified representation of an entity, a phenomenon, a transaction, or an event. The information results from a data analysis process; often, it has meaning only for the one who works in the data generation domain. Knowledge is obtained when a person uses the information to make decisions and carry out actions when information is used to be put “into practice.”
Analytics tools are needed to implement this process and to ensure that Big Data can be transformed into information to be used in business processes by building knowledge to improve performance. In addition to the 5V model, it is necessary to consider a further V: the value. Here it is the fundamental Big Data Analytics methodologies; through their use, a company can extract value or make more informed, timely, and aware decisions from the vast world of Big Data.
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