Why is it so hard to define Big Data?

Pinning down what qualifies as Big Data — and whether it’s an educational panacea or a corporate-driven technological phase — is sure to be at the center of educational technology discussions for years to come.

big-data-definitioneCampus News assistant editor Jake New, in the first part of our “Higher Education’s Big (Data) Bang” series, explored the working definition of Big Data analytics, as understood by some of the field’s most prominent voices.

“Big Data is this exponential increase of information that’s been going on since the 1950s,” said Jim Spohrer, the director of Global University Relations Programs at IBM, a company that has partnered with campuses to drive the study and adoption of data analytics.

The varying definitions and understandings of Big Data and what it might mean for higher education were recently summarized in the MIT Technology Review, as the publication examined survey results centered around what Big Data is.

Here are some of the various Big Data definitions — as told by data-centric organizations and corporations — mentioned in the Technology Review.

1. Gartner. In 2001, a Meta (now Gartner) report noted the increasing size of data, the increasing rate at which it is produced and the increasing range of formats and representations employed. This report predated the term “dig data” but proposed a three-fold definition encompassing the “three Vs”: Volume, Velocity and Variety.This idea has since become popular and sometimes includes a fourth V: veracity, to cover questions of trust and uncertainty.

2. Oracle. Big data is the derivation of value from traditional relational database-driven business decision making, augmented with new sources of unstructured data.

See page 2 for how Intel and Microsoft define Big Data…