DocumentCode :
3080041
Title :
Forecasting consumer behavior with innovative value proposition for organizations using big data analytics
Author :
Balar, Ankur ; Malviya, Nirmesh ; Prasad, Santasriya ; Gangurde, Ajinkya
Author_Institution :
Grad. Sch. of Bus., Grenoble Ecole de Manage., Grenoble, France
fYear :
2013
fDate :
26-28 Dec. 2013
Firstpage :
1
Lastpage :
4
Abstract :
The term `Big Data´ is used to represent collection of such a huge amount of data that it becomes impossible to manage and process data using conventional database management tools. Big Data is defined by three important parameters `Volume´ - Size of Data, `Velocity´ - Speed of increase of data and `Variety´ - Type of Data. Big data analytics is the process of analyzing this ever growing Big Data. The goal of every organization is to maximize its value for its stake holders. The paper aims to demonstrate that Big data analytics can be used as a catalyst for generating and increasing value for organizations by improving various business parameters. Furthermore, by utilizing case studies the paper also aims to establish that big data analytics supports creation, enhancement and improvement of various business services to significantly improve customer experience as well as value creation for organizations.
Keywords :
Big Data; business data processing; consumer behaviour; data analysis; database management systems; innovation management; value engineering; Big Data analytics; business service creation; business service enhancement; business service improvement; consumer behavior forecasting; customer experience; data collection; data management; data processing; data size; data variety; data velocity; data volume; database management tools; innovative value proposition; organization business parameters; value creation; Consumer behavior; Data handling; Data storage systems; Information management; Organizations; Technological innovation; Big data; data analytics; distributed analysis; value creation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on
Conference_Location :
Enathi
Print_ISBN :
978-1-4799-1594-1
Type :
conf
DOI :
10.1109/ICCIC.2013.6724280
Filename :
6724280
Link To Document :
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