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Big Data in Banking for Marketers

S.R Hiray, Karan Makode

Abstract


Big data was born out of the necessity of data sets growing so large and complex that traditional tools are no longer sufficient to process this data. By aggregating large amounts of data from many different sources makes big data very powerful for business decision-making. Thus revealing insights and behaviours faster and better than otherwise possible with traditional BI. 

In Marketing & Sales the main strategic goals are to acquire new customers, develop as well as to retain existing ones.  During the last years Big Data has become the buzzword across various industries. But it is difficult to know exactly what Big Data can do to improve business value and which Big Data applications marketers should consider to invest both their time and money in. The goal of this seminar is to show a comprehensive list of data driven use cases and their value, which are deployed by successful marketing teams today.

Keywords


Business Intelligence; Big Data

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References


“Machine Learning Approach for Predicting Bank Credit Worthiness” By Regina Esi Turkson, Edward Yeallakuor Baagyere,

“Bank efficiency assessment using a hybrid approach of random forests and data envelopment analysis” By Imad Bou Hamad, Abdel Latef Anouze

“Data mining application in banking sector with clustering and classification methods” By Aslı Çaliş, Ahmet Boyaci, Kasım Baynal

“Understanding Customers Using Facebook Pages: Data Mining Users Feedback Using Text Analysis” By Hsin-Ying Wu *, Kuan-Liang Liu, Charles Trappey


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