ABSTRACT
Big data is often characterized by the "3 Vs": Volume: More data than can be handled by infrastructure for conventional data, Velocity: Usually being generated or requiring interception at high speed, and Variety: Largely unstructured, coming from a multitude of sources whose data types have little if no relationship to one another. The closest analogy to big data is data warehousing. While data warehousing is typically an activity associated with enterprise relational databases and therefore operations and analytics on highly structured data, big data applies order at the time of analysis to a view of unstructured data. In essence, big data is about finding new methods other than the classic brute-force approach to data analysis: rather than a few extremely powerful servers trying to crunch through a massive data set, a large number of adequately powerful low-end systems each crunch through a comparatively very small data set.
