Definition - What does Small Data mean?
Small data describes data use that relies on targeted data acquisition and data mining. It describes a shift in how businesses and other parties look at data use, and is intended to be a counterpoint to the trend toward big data, which revolves around the idea that businesses can use massive amounts of acquired data to pinpoint customer behavior or drive business intelligence in key ways. By contrast, a small data approach involves acquiring specific data sets through less effort, which proponents believe to be be a more efficient business practice.
Techopedia explains Small Data
For a common-sense look at how this might work, consider some of the specific systems that might be used in big data acquisition. A company might invest in a whole lot of server storage, and use sophisticated analytics machines and data mining applications to scour a network for lots of different bits of data, including dates and times of user actions, demographic information and much more. All of this might get funneled into a central data warehouse, where complex algorithms sort and process the data to display it in detailed reports.
While these kinds of processes have benefited businesses in a lot of ways, many enterprises are finding that these measures require a lot of effort, and that in some cases, similar results can be achieved using much less robust data mining strategies. For example, rather than acquiring all of this hardware and software to get complete surveillance of customers, a business could employ a simple survey, mailing list responses or other organic volunteered information to craft its customer relationship strategy. It could also used a more scaled down software infrastructure to get more basic data.
Small data is one of the ways that businesses are now drawing back from a kind of obsession with the latest and newest technologies that support more sophisticated business processes. Those promoting small data contend that it’s important for businesses to use their resources efficiently and avoid overspending on certain types of technologies.