The difference between ‘dense’ and ‘sparse’ data

As most buy-side financial executives are well aware, big data is an umbrella term. Though the definitions vary depending on who’s being asked, it basically describes a large amount of information – whether in substance or velocity – that requires data governance in order to effectively process it and optimize its usage. That said, there are subsections within this term that categorize what types of information are sparse and which ones are dense.

Global business news outlet Quartz recently addressed this issue so business owners can more effectively manage their big data so that it can be better used when making key decisions.

As Quartz describes it, dense data is essentially many different pieces of information about a particular subject, whatever it happens to be. For example, if in a survey people were asked a number of open-ended questions, the answers given could be adequately described as being dense.

Most useful data is sparse
Sparse data, on the other hand, is called as such not only because the information that it represents is less comprehensive, but also because it’s fairly rare. As such, this makes it more valuable for business owners, the source noted. Companies will often make make certain assumptions about clientele based on the sparse data that’s collected.

No matter what form it comes in, though, companies that use big data are at a distinct advantage over those that don’t. Quartz cited a study performed by researchers from New York University. After controlling for outside influences, the researchers discovered that big data-using companies were more productive than those that relied on big data less often.

It’s not enough, however, to simply have sparse or dense data, Quartz advised. In other words, while productivity is better facilitated through its usage, there’s something to be said for quality. Thus, the more features that are being gathered about a specific topic – whether it’s about a customer or an investment – the better the results will ultimately be in the end.

Big data is no longer a specialized term that’s only familiar to industry insiders, or those who specialize in data quality management. According to a report on big data from the McKinsey Global Institute, the explosion in companies analyzing large data sets “will become a key basis of competition, underpinning new waves of productivity growth, innovation and consumer surplus.”

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