Definition of Big Data
We call Big Data the management and analysis of huge volumes of data that cannot be treated in a conventional way, since they exceed the limits and capabilities of the software tools commonly used for data capture, management and processing. This concept encompasses technological infrastructures and services that have been created to provide a solution to the processing of huge sets of structured, unstructured or semi-structured data (messages on social networks, mobile signals, sensor audio files, digital images, form data). , emails, survey data, logs, etc…
The objective of Big data, like conventional analytical systems, is to convert ‘Data’ into information that facilitates decision-making, even in real time. However, more than a matter of size, it is a business opportunity. Companies are already using ‘Big Data’ to understand the profile, needs and feelings of their customers regarding the products and/or services sold. This acquires special relevance since it allows adapting the way in which the company interacts with its clients and how they provide service to them.
Difference between analytical applications and Big Data
The differences are associated, in most reference articles, with three words, the three ‘Vs’ of Big Data: Volume, Variety and Velocity (3Vs). However, based on the experience acquired by the pioneering companies in this adventure, the original definition has been expanded, adding new features such as the Veracity and Value of the data (5Vs).
More information on Big Data:
– by Jorge Carlos Lopez Lopez
– by Miguel Ángel Cedrún Blanco from SBS
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