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Research Paper | Computer Science & Engineering | India | Volume 4 Issue 6, June 2015 | Popularity: 7 / 10

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Business Intelligence Using Data Mining Techniques on Very Large Datasets

Arti J. Ugale, P. S. Mohod

Abstract: Business Intelligence (BI) is a concept of applying a set of technologies to convert data into meaningful information. BI methods include information retrieval, data mining, statistical analysis as well as data visualization. Large amounts of data originating in different formats and from different sources can be consolidated and converted to key business knowledge. Data mining is used to search for patterns and correlations within a database of information. Business intelligence (BI) focuses on detail integration and organization. DM aids BIs objectives. DM and BI work together to process data and analyze it in a way that eases the workload for the users and aids with the understanding of the materials/findings. This is accomplished through recognizing relationships in the data and identifying opportunities and risks of the company. It also allows users to manipulate the data to fulfil their specific user-oriented objectives. Data mining is the process of searching through data using various algorithms to discover patterns and correlations within a database of information. Business intelligence, on the other hand, focuses more on data integration and organization. It will combine data analyse to help managers make operational, tactical, or strategic business decisions. Data mining can be used to aid the objectives of a business intelligence system. Classification and patterns extraction from customer data is very important for business support and decision making. Timely identification of newly emerging trends is very important in business process. Large companies are having huge volume of data but starving for knowledge. To overcome the organization current issue, the new breed of technique is required that has intelligence and capability to solve the knowledge scarcity and the technique is called Data mining. The objectives of this paper are to identify the high-profit, high-value and low-risk customers by one of the data mining technique customer clustering. The paper explores the concepts of BI, its components, emergence of BI, benefits of BI, factors influencing BI, technology requirements, designing and implementing business intelligence, and various BI techniques.

Keywords: Data Mining, Business Intelligence, Distributed algorithm, Clustering, Content Based Indexing

Edition: Volume 4 Issue 6, June 2015

Pages: 2932 - 2937

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