Big Data Optimization for Customer Discounts in Cloud Computing Environment

Big Data Optimization for Customer Discounts in Cloud Computing Environment

Raghvendra Kumar (LNCT College, India), Prasant Kumar Pattnaik (KIIT University, India) and Priyanka Pandey (LNCT, India)
DOI: 10.4018/978-1-5225-2013-9.ch009
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Abstract

Large companies have different methods of doing this, one of which is to run sales simulations. Such simulation systems often need to perform complex calculations over large amounts of data, which in turn requires efficient models and algorithms. This chapter intends to evaluate whether it is possible to optimize and extend an existing sales system called PCT, which is currently suffering from unacceptably high running times in its simulation process. This is done through analysis of the current implementation, followed by optimization of its models and development of efficient algorithms. The performances of these optimized and extended models are compared to the existing one in order to evaluate their improvement. The conclusion of this chapter is that the simulation process in PCT can indeed be optimized and extended. The optimized models serve as a proof of concept, which shows that results identical to the original system's can be calculated within < 1% of the original running time for the largest customers.
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Defining Big Data

Today, innovative era of technology, everywhere that are visible or not visible to us its only technology, everyone are using different-different technology for their daily uses, like if we are taking example of human being daily routine, when the person is wake up at early morning that the person uses different technology like mobile phone, laptop, notebook etc. And also uses the internet connection for checking any updates from their friends at one single time, for that they are transferring or uses huge amount of data in single seconds. Like that if we are taking an example of India there are internet users are increasing very rapidly, now everyone are using the smart phone, laptop and many other digital devices for connecting the different users at a single time, when the different users are connecting through internet at that time they are transferring the huge amount of data to the internet, that data size in the form of zeta bytes, peta bytes etc., this huge amount of data is known as Big data. That contains three main properties Volume, Variety and Velocity. Variety or Volume mainly focuses on the leads to the question of how to process big data analytics and velocity is mainly focuses on the possibilities rather than technologies, about performance and about business impact that we are using. As we already know that data processing for the large amount of unstructured data is very crucial, because consumers and citizens want the immediate response from the server or service providers. If they tweet their massage about what in their own mind and they want that massage served by the web care teams for their immediate response. As we know that today technology are growing very fast and rapidly. Everyone are using high speed electronic devices and they all wants the high processing and accessing speeds. Time is money and acceleration is synonymous with reasonable advantage. Real time analysis is not fast enough but for predicting what will happen in future is real ambition, if we are moving from the predictive to prescriptive analysis. Most of the data scientists are working on the prescriptive analysis for predicting the future analysis and some of the agencies are using the mobile phone data for statistical analysis. Insight from location data and people are moving around have proven to be an excellent alternative for charting the consumer behavior.

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