ff928931__Data_Is_to_Produce_Small_Data__Big_Data
[0] Stakes [Small Data] Project costs are limited. Laboratories and institutions can usually recover from the occasional small data failure. [Big Data] 
Big data projects can be obscenely expensive. A failed big data effort can lead to bankruptcy, institutional collapse, mass firings, and the sudden disintegration of all the data held in the resource. Though the costs of failure can be high in terms of money, time, and labor, big data failures may have some redeeming value. Each failed effort lives on as intellectual remnants consumed by the next big data effort.
The Most Common Purpose of Big Data Is to Produce Small Data
Big Data