Defining Small Data

With a flurry of new articles on small data in various publications recently – including Wired, Technorati, and AllThingsD – there’s a growing number of voices contributing to the small data movement (a great thing!). But with these new perspectives, I feel like it’s a good time to re-ground the conversation in an actual definition of what we are talking about when we refer to “small data” – or at least what I’m talking about!

So in this post I wanted to share my first cut at a proper definition. Yes, I’ve framed the pillars for small data in many other places, going back to my first guest piece in Forbes on the topic a year ago (!), and more recently I’ve embraced the idea of describing small data as “the last mile of big data.” But these were descriptions or principles vs. definitions for the most part.

So, after spending the last couple month working on Digital Clarity Group‘s new multi-client study on “Bringing the Power of Big Data to the Masses” (sponsored by my friends at Adobe, Actuate, HubSpot, and Visible), seeing how marketers are looking to make analytics more accessible and actionable – and creating some new starter use cases, an interesting thing happened: a definition emerged!

In fact, while our final report is still a week or so away from being available from DCG and our sponsors, I shared the definition with our audience at the Digital Pulse Summit this past week during my panel on small data, and given the response, I wanted to provide it here as well.

A New Definition for Small Data

Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks. 

Note, as we describe in our report, this definition applies to the data we have, as well as the end-user apps and analyst workbenches for turning big data set into actionable small data. The key “action” words here are connect, organize, and package, and the “value” (the 4th V of big data) is rooted in making insights available to all (accessible), easy to apply (understandable), and focused on the task at hand (actionable).

In fact, I hope it’s as much a mission statement, as it is a definition. What do you think? Did we nail it?

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