%0 Journal Article %1 noauthororeditor %A S.Vijayarani1, Dr. %A S.Sharmila2, Ms. %D 2016 %J Informatics Engineering, an International Journal (IEIJ) %K Big Classification, Clustering Technologies, Visualization, data, %N 03 %P 01-20 %R 10.5121/ieij.2016.4301 %T RESEARCH IN BIG DATA – AN OVERVIEW %U http://aircconline.com/ieij/V4N3/4316ieij01.pdf %V 04 %X Big data is a prominent term which characterizes the improvement and availability of data in all three formats like structure, unstructured and semi formats. Structure data is located in a fixed field of a record or file and it is present in the relational data bases and spreadsheets whereas an unstructured data file includes text and multimedia contents. The primary objective of this big data concept is to describe the extreme volume of data sets i.e. both structured and unstructured. It is further defined with three “V” dimensions namely Volume, Velocity and Variety, and two more “V” also added i.e. Value and Veracity. Volume denotes the size of data, Velocity depends upon the speed of the data processing, Variety is described with the types of the data, Value which derives the business value and Veracity describes aboutthe quality of the data and data understandability

@article{noauthororeditor, abstract = {Big data is a prominent term which characterizes the improvement and availability of data in all three formats like structure, unstructured and semi formats. Structure data is located in a fixed field of a record or file and it is present in the relational data bases and spreadsheets whereas an unstructured data file includes text and multimedia contents. The primary objective of this big data concept is to describe the extreme volume of data sets i.e. both structured and unstructured. It is further defined with three “V” dimensions namely Volume, Velocity and Variety, and two more “V” also added i.e. Value and Veracity. Volume denotes the size of data, Velocity depends upon the speed of the data processing, Variety is described with the types of the data, Value which derives the business value and Veracity describes aboutthe quality of the data and data understandability}, added-at = {2018-07-11T10:33:51.000+0200}, author = {S.Vijayarani1, Dr. and S.Sharmila2, Ms.}, biburl = {https://www.bibsonomy.org/bibtex/299238f2ef91bb0fde25857b8d5e7f911/ieij1}, doi = {10.5121/ieij.2016.4301}, interhash = {d22f789194c4a1d788ff724574f4859b}, intrahash = {99238f2ef91bb0fde25857b8d5e7f911}, journal = {Informatics Engineering, an International Journal (IEIJ)}, keywords = {Big Classification, Clustering Technologies, Visualization, data,}, language = {eng}, month = sep, number = 03, pages = {01-20}, timestamp = {2018-07-11T10:33:51.000+0200}, title = {RESEARCH IN BIG DATA – AN OVERVIEW}, url = {http://aircconline.com/ieij/V4N3/4316ieij01.pdf}, volume = 04, year = 2016 }