But data are meaningless until compared to other data, visualized in context or analyzed for significance.
We can think of an algorithm as a Rosetta stone for data, transforming them into a meaningful form for humans.However, unlike the Rosetta stone, there are no limits to how many different keys we can create to derive insight from a single dataset. With so many data of so many varieties, the number of Rosetta stones we can use—and the number of people with basic data science skills needed to transform data into meaningful action or insight—increases exponentially.
As O’Reilly’s Edd Dumbill wrote in a January Forbes piece, “In the broader business consciousness, at the end of 2012, ‘big data’ really means ‘smart use of data’” (www.forbes.com/sites/edddumbill/2012/12/31/big-data-big-hype-big-deal).