Data Mining: Exploring Big Data Analytics, Hadoop and Mapreduce
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 3, Issue 8
Abstract
Most internal auditors, especially those working in customer-focused industries, are aware of data mining and what it can do for an organization — reduce the cost of acquiring new customers and improve the sales rate of new products and services. However, whether you are a beginner internal auditor or a seasoned veteran looking for a refresher, gaining a clear understanding of what data mining does and the different data mining tools and techniques available for use can improve audit activities and business operations across the board. The tremendous opportunities to gain new and exciting value from big data are compelling for most organizations, but the challenge of managing and transforming it into insights requires a new approach to analytics that has a far reaching impact on IT infrastructure. Traditional systems are unable to cope cost-effectively—if at all— with new dynamic data sources and multiple contexts for big data. Emerging technologies such as the Hadoop* framework represent completely new approaches to capturing, managing, and analyzing big data. Big data challenges plus new technologies are causing a paradigm shift that is driving organizations to reexamine their IT infrastructure and analytics capabilities. With the fast growth of networks now-a-days organizations has filled with the collection of millions of data with large number of combinations. This big data challenges over business problems. It requires more analysis for the highperformance process. The new methods of hadoop and MapReduce methods are discussed from the data mining perspective.
Authors and Affiliations
Ms. Rupali Chikhale
Keywords
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