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Citations since 2017
5 Research Items
A forward-thinking Data Analyst and customer service expert in financial services, education, aviation, and government sector.
Skills and Expertise
This is a magazine illustrating the progress of Apple using different data visualization techniques.
E-commerce is the way of purchasing products via an online platform. With tons of technological improvements, e-commerce industry has seen a vast improvement in recent years. Firms in this domain aim at increasing profit by analyzing the previous customer purchase data. Therefore, by deploying a data mining technique, customer data can be analyzed...
This paper covers the analysis of a Spanish online store data to identify customer segments and help improve marketing strategies for future purposes. Several clusters were realized in this paper, but no all were found useful for managerial purposes. The result presents five clusters. Group names were assigned to each cluster, and their value to th...
The aim of this project is to analyze the relationship between airlines based on their total number of passengers, number of employees, passenger handling rights, service quality and revenue. It places strong focus on analyzing the customer service quality of the largest airlines in the world, based on their number of employees. Furthermore it hope...
The aim of this project is to create analysis and estimates using the multiple regression model and the binary logistic regression model. The first piece of analysis will involve the multiple regression model, which will be used to explore how well the indicators of fertility and mortality such as total fertility rate, maternal mortality ratio and...
This study presents the analysis of three clustering algorithms - K-means Clustering, Fuzzy C-means Clustering, and Hierarchical Clustering, which were built using R programming language to understand customer behavior and segment them based on the purchase pattern through Recency, Frequency and Monetary (RFM) model. The analysis was done using the KDD methodology approach and all three algorithms were evaluated internally and externally using various validation measures like Silhouette Width, Dunn Index, Adjusted Rand Index and Variation Index.
The aim of this project is to analyze the relationship between airlines based on their total number of passengers, number of employees, passenger handling rights, service quality and revenue. It places strong focus on analyzing the customer service quality of the largest airlines in the world, based on their number of employees. Furthermore it hopes to help airline companies use their data in a more resourceful way. It also further emphasizes the need for customer service quality in airline companies, proving that quality is better than quantity. This means that an airline with more resources might not necessarily render better services but if it does not use its resources in the right way.