Authors :
Prof. Mayuri Bharat Dandwate, Prof. Rutuja Vilas Kotkar
Volume/Issue :
Volume 2 - 2017, Issue 12 - December
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/7hFvgS
Thomson Reuters ResearcherID :
https://goo.gl/3bkzwv
Abstract :
Big data, which refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology. Big Data is high volume, high velocity, high variety information assets that demand cost effective forms of information processing that enable enhanced insight, decision making and process automation. Big data presents a grand challenge for database and data analytics research. Big Data poses a grand challenge on the design of highly scalable algorithms and systems to integrate the data and uncover large hidden values from datasets that are diverse, complex, and of a massive scale.
Keywords :
Big Data, Volume, Velocity, Variety, NoSQL, Storage.
Big data, which refers to the data sets that are too big to be handled using the existing database management tools, are emerging in many important applications, such as Internet search, business informatics, social networks, social media, genomics, and meteorology. Big Data is high volume, high velocity, high variety information assets that demand cost effective forms of information processing that enable enhanced insight, decision making and process automation. Big data presents a grand challenge for database and data analytics research. Big Data poses a grand challenge on the design of highly scalable algorithms and systems to integrate the data and uncover large hidden values from datasets that are diverse, complex, and of a massive scale.
Keywords :
Big Data, Volume, Velocity, Variety, NoSQL, Storage.