The whole ball of wax we create leaves a digital footprint. Big data had ascended as a catchword in recent years. Principally, it means a prodigious aggregate of information that is stimulated as trails or by-products of online and offline doings — what we get using credit cards, where we travel via GPS, what we ‘like’ on Facebook or retweet on Twitter, or what we bargain either through “apnidukaan” via amazon, and so on. In this era and stage, the Data as a Service (DaaS) battle is gaining force, spurring one of the fastest growing industries in the world.“Big data” is a jargon for data sets that are so gigantic or multi-layered that old-style data processing application software’s are deprived to concord with them. Challenges contain apprehension, storage, analysis, data curation, search, sharing, and transmission, visualization, querying, and updating information privacy. The term “big data” usually refers self-effacingly to the use of extrapolative analytics, user behaviour analytics, or sure other advanced data analytics methods that extract value from data, and infrequently to a separable size of data set
