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Analysing Big Data sets Using Descriptive Analytics

Author Affiliations

  • 1Department of Computer Science & Engineering, Shri Shankaracharya Group of Institutions, Chhattisgarh Swami Vivekan and Technical University, Bhilai - 490006, Chhattisgarh, India
  • 2Department of Computer Science & Engineering, Shri Shankaracharya Group of Institutions, Chhattisgarh Swami Vivekan and Technical University, Bhilai - 490006, Chhattisgarh, India

Res. J. Computer & IT Sci., Volume 4, Issue (9), Pages 5-8, September,20 (2016)


Big data is generally a term used to delineate massive volume of data that is difficult to process using conventional techniques of data processing. Big data, for any enterprise, refers to the data sets that exceeds its current data processing capacity. As big data is arriving from many different sources with a huge velocity, volume and variety, it is necessary to handle them and extract meaningful information that could be beneficial for an enterprise. For this various kinds of analytics are done. The objective of any analytics solution is to provide the enterprise with actionable insights for better business outcomes and smarter decisions. This paper focusses on analysing big data sets considering data from banking sector thus helping banks in various aspects like customer segmentation, sentiment analysis, transactional analysis, security and fraud management etc. Here Descriptive Analytics is done which uses business intelligence and data mining for learning from past behaviours and thus helping in decision making.


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