This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry.

Chapter1: Predicting Implicit Negative Relations in Online Social Networks.- Chapter2: Automobile insurance fraud detection using social network analysis.- Chapter3: Improving circular layout algorithm for social network visualization using genetic algorithm.- Chapter4: Live Twitter Sentiment Analysis.- Chapter5: Artificial Neural Network Modeling and Forecasting of Oil Reservoir Performance.- Chapter6: A Sliding-Window Algorithm Implementation in MapReduce.- Chapter7: A Fuzzy Dynamic Model for Customer Churn Prediction in Retail Banking Industry.- Chapter8: Temporal Dependency between Evolution of Features and Dynamic Social Networks.- Chapter9: Recommender System for Product Avoidance.- Chapter10: A new 3D value model for customer segmentation:Complex Network Approach.- Chapter11: Finding Influential Factors for Different Types of Cancer: A Data Mining Approach.- Chapter 12: Enhanced load balancer with multi-layer processing architecture forheavy load over cloud network.- Chapter13: Market Basket Analysis Using Community Detection Approach: A Real Case.- Chapter14: Predicting Future with Social Media based on Sentiment and Quantitative Analysis.

This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry. The chapters cover effective approaches in dealing with the inherent complexity and increasing demands of big data management from an applications perspective.Various case studies included have been reported by data analysis experts who work closely with their clients in such fields as education, banking, and telecommunications. Understanding how data management has been adapted to these applications will help students, instructors and professionals in the field. Application areas also include the fields of social network analysis, bioinformatics, and the oil and gas industries.

Features state-of-the-art techniques for data management and analysis using current algorithms, models, and architecture Contains case studies describing how data analysis can improve the insurance, banking, e-commerce, biomedical, and oil industries Includes topics on education such as building repositories to support instructors and curriculum development in big data