There was a time when the only things that were granular either were, or reminded you of, grains. Grains have been on the menu ever since humans discovered wild cereal plants and began to cultivate them, laying the foundations for that unstoppable behemoth that we call civilization. The current state of civilization, whatever its ills, is the information age, and when you see the word granular today, or its derived noun granularity, chances are that the “grains” underlying the words are not ones you would want to eat—though you might well want to consume them. These days, granular and granularity are words dear to the heart of information consumers and producers, and they are frequently used in contexts in which data and information are being discussed.
What is the appeal of words like granular and granularity when English already has words that mean nearly the same thing and that are more typically applied to information? The words I’m thinking of are specific and its noun, specificity. It may be that despite all of the great advances of our intelligence, humans are still bound to their sense organs and we like things described in ways that relate directly to seeing, hearing, feeling, tasting, touching, and smelling. Language that brings our understanding a step closer to sense data is more engaging than language that is entirely abstract.
Here are a few citations from current news stories that take advantage of the grainy metaphor that we informavores like so well:
While log data analysis is nothing new, it can be done to dizzying new levels of granularity. (PC World)
The association of group practice administrators asked CMS to provide more granular identification of all entities that fund, receive and administer insurance claims. (FierceHealthIT.com)
Data with this level of granularity can be used to improve stacking for storage and trailer loading, warehouse throughput sequencing, object identification for track and damage reporting, and reusable container tracking. (Eworldwire.com)
In all of these cases, specific or specificity would work as well in place of the g-words. But for the reasons we noted above, as well as for a certain buzzword quality, people who deal with data and information like to be granular these days, rather than specific. The same reasons may explain why they want to drill down into data rather than analyze it hierarchically, and how they got the idea that data could be mined. Those two verbs, mine and drill down, evoke clear images of things that require physical force in space.
A word like grain evokes an idea of something that is perceptible to two of our senses: sight and touch. We naturally identify things that are different from their surroundings when a sense organ detects that difference. Because of this, old words whose core meaning gives us an idea of a thing that can be pulled out from its context constantly find new jobs and do not grow stale. The 14th century word patch got a huge career boost when software patches came along, and 12th century cluster can currently be seen as the noun of choice for characterizing a group of servers or computers that work together closely, or a group of sectors that are identified in the index of a data storage device. In all cases, speakers and writers settle on a usage that is somewhat figurative, but vivid and meaningful because of its sensory associations.Email this Post
[…] a catchphrase, and examined the phrase, yeah, no. At Macmillan Dictionary blog, Orin Hargraves got granular, Robert Lane Greene talked go, and Stan Carey considered commas and at Sentence First taught us how […]
To mine the data comes from data mining, the computer science field that implies the use if artificial intelligence / machine learning to analyse big data sets http://en.wikipedia.org/wiki/Data_mining
This term is widely accepted.
I suppose the term granular is used metaphorically, as seldom the data analysed is even, of the same quality.