“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.”
Put even more simply, big data is about machines; small data is about people.
Simplicity Amid Ubiquitous Data
There is no small vs. big debate going on here. Clearly, Bonde and others are intrigued about the possibilities of big data. However, Bonde and others say the ubiquity of data from users, devices and sensors “drives the need for less complexity and a simpler approach to deliver and visualize and operationalize data and its insights.”
“Yet all the steam coming out of the big data hype machine seems to be obscuring our view of the big picture: in many cases big data is overkill,” Bonde writes. “And in most cases big data is useful only if we (those of us who aren’t data scientists) can do something with it in our everyday jobs.”
As mentioned in this space, Gigaom Research, Gartner and others have shared research confirming the importance of users having the functionality of self-service data discovery tools in their work. Izenda is a leading BI platform built for independent software vendors, solutions providers and enterprise users. Our embedded software solution gives users the ability to analyze data in real time, providing self-service BI to organizations.
3 Components of Small Data
According to Bonde, the three components of small data are: 1) It’s a design philosophy inspired by consumer apps and services delivering data, content and insights to the on-the-go user. 2) It’s the technology, processes, and use cases for turning big data into alerts, apps, and dashboards, (the “last mile”) for business users. 3) The literal definition of small data referring to the size of our data sets as well.
Small-data enthusiasts see the value of a world in which data is democratized and in the hands of the user. It’s not about “large organizations running parallel software on tens of thousands of servers,” Bonde writes. It’s about people at all levels of the organization collaborating in an ecosystem of small data.
It’s OK to Start Small
Starting small in data analytics is often a winning strategy, a post by Gallup, the research and management consulting firm, recently observed.
“Starting small provides some real benefits if done correctly, because the organization can find its analytical footing and learn what it needs from a technology, data, management and talent standpoint to drive business impact. Moreover, a small application on a specific problem allows an organization to better understand the ROI of its analytics approach before scaling up to a larger solution,” the authors wrote.