Data Mining Techniques with Electronic Customer Relationship Management for Telecommunication Company

Organizations must improve decisional quality, and the continuous usage of data mining techniques is a crucial issue for management. This issue mostly involves an individual's motivation to engage in the behavior. This could perhaps be characterized in terms of the working regimen. technology utilization and employee activity are the two main difficulties that this dilemma revolves around. This study aims to address the aspect associated with data mining and E-CRM in the telecom industry. The methods that are used in the current study,  analysis studies of the data mining techniques are applied to E-CRM that has been identified. Moreover, PHP with the update of the DeLone and McLean methods has been used in the current study. The results show the significance in affecting the continuance used intention of data mining techniques. User satisfaction, technology, and data mining are critical predictors of employment intentions

Consumer finance: challenges for operational research

Consumer finance has become one of the most important areas of banking, both because of the amount of money being lent and the impact of such credit on global economy and the realisation that the credit crunch of 2008 was partly due to incorrect modelling of the risks in such lending. This paper reviews the development of credit scoring—the way of assessing risk in consumer finance—and what is meant by a credit score. It then outlines 10 challenges for Operational Research to support modelling in consumer finance. Some of these involve developing more robust risk assessment systems, whereas others are to expand the use of such modelling to deal with the current objectives of lenders and the new decisions they have to make in consumer finance. <br/

NEMISA Digital Skills Conference (Colloquium) 2023

The purpose of the colloquium and events centred around the central role that data plays today as a desirable commodity that must become an important part of massifying digital skilling efforts. Governments amass even more critical data that, if leveraged, could change the way public services are delivered, and even change the social and economic fortunes of any country. Therefore, smart governments and organisations increasingly require data skills to gain insights and foresight, to secure themselves, and for improved decision making and efficiency. However, data skills are scarce, and even more challenging is the inconsistency of the associated training programs with most curated for the Science, Technology, Engineering, and Mathematics (STEM) disciplines. Nonetheless, the interdisciplinary yet agnostic nature of data means that there is opportunity to expand data skills into the non-STEM disciplines as well.College of Engineering, Science and Technolog

Big Data Analytic Framework for Organizational Leverage

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