What is big data analytics? Fast answers from diverse data sets


There’s data, and then there’s big data. So, what’s the difference?

Big data defined

A clear big data definition can be difficult to pin down because big data can cover a multitude of use cases. But in general the term refers to sets of data that are so large in volume and so complex that traditional data processing software products are not capable of capturing, managing, and processing the data within a reasonable amount of time.

These big data sets can include structured, unstructured, and semistructured data, each of which can be mined for insights.

How much data actually constitutes “big” is open to debate, but it can typically be in multiples of petabytes—and for the largest projects in the exabytes range.

Often, big data is characterized by the three Vs:

  • an extreme volume of data
  • a broad variety of types of data
  • the velocity at which the data needs to be processed and analyzed

The data that constitutes big data stores can come from sources that include web sites, social media, desktop and mobile apps, scientific experiments, and—increasingly—sensors and other devices in the internet of things (IoT).



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