Today’s hype is Big Data. As with other hypes, such as ‘sharing economy’, ‘cloud’, ‘blockchain’, the hype is simultaneously promoted as a commercial instrument that is indispensable for companies and as a pervasive phenomenon that redefines the fabric of society.
Every big corporation sits on a heap of big data about their customers. Statistical analysis of the data enables them to know their customers better than they know themselves, and this puts them in a unique position. Smaller competitors can, by definition, not know their customers as well as a major corporation with huge big data, like Google, Facebook, Ebay or Amazon, can.
Big data has always been around. Only the computing power to process it and derive conclusions from it is new. Also small businesses and private people are surrounded with big data, but they don’t realize it. I like to define ‘big data’ as follows:
| Big data are data that allow for conclusions that go further than intuition.
So, even if there aren’t millions of data points, we can speak of ‘big data’ in a meaningful way. For example, a mom and pop store has data about popular products. They might know patterns of consumption, such as an increase in sales of sweets around holidays. They have always dealt with such data with their intuition and tend to doubt if there is more to it. Analyzing their ‘small big data’ could give them some new insight that is useful for their business.
However, tiny companies, even if they are convinced of the importance of their modestly big data, can’t afford an analyst team of data scientists. They could use websites to help them analyze their data and exchange insights on online platforms. This could lead to a great increase in efficiency, for example in the area of supply chain and stock management. ‘Big data’ should not be something only the big guys can play with, all data that, upon analysis, can surprise us, is big.