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Vol 03, Issue 01; January-April 2012 Research Journal of Computer Systems Engineering - RJCSE http://technicaljournals.org cFACT -2012, Loyola College, Chennai, TN ISSN: 2230-8563; e-ISSN-2230-8571 2010-2012 - TECHNICALJOURNALS ® , Peer Reviewed International Journals-IJCEA, IJESR, RJCSE, PAPER, ERL, IRJMWC, IRJSP, IJEEAR, IJCEAR, IJMEAR, ICEAR, IJVES, IJGET, IJBEST TJ-PBPC, India; Indexing in Process - EMBASE, EmCARE, Electronics & Communication Abstracts, SCIRUS, SPARC, GOOGLE Database, EBSCO, NewJour, Worldcat, DOAJ, and other major databases etc., 304 ROLE OF DATA WAREHOUSING AND DATA MINING TECHNOLOGY IN BUSINESS INTELLIGENCE PALAK GUPTA ASSISTANT PROFESSOR, JAGANNATH INTERNATIONAL MANAGEMENT SCHOOL, MOR, POCKET-105, KALKAJI, NEW DELHI-19 vaishpalak@rediffmail.com ABSTRACT This paper includes the combined study of Business Intelligence (BI), Data Warehouse and Data Mining technologies. BI techniques are generally computer based that provide past, current and future trends of the enterprise. Its applications include activities of decision support system, query and reporting, complex event processing, online analytical processing, process mining, business performance management and statistical and predictive analysis. A data warehouse is a repository of relational databases designed for query and analysis. It separates analysis workload from transaction workload and enables an organization to consolidate data from different varying sources. This data warehouse is analyzed by data mining, which is a latest technique allowing enormous data sets to be explored so as to yield hidden and unknown predictions that can be used in future for efficient decision making. The data that is used in current business domains is not precise, accurate and complete. Instead, data is considered uncertain and therefore this uncertainty is propagated to the results produced by Business Intelligence. So, now companies use techniques of data mining that involves pattern recognition, statistical and mathematical techniques to search data warehouses and help the analysts in recognizing significant trends, facts, relationships, exceptions and anomalies that might otherwise go unnoticed. This paper includes the study of data warehousing and data mining of uncertain and voluminous data in business intelligence. To provide better analysis of data, data mining methodology is used which is a computer assisted process of exploring and analyzing volumes of data and then extracting their correct meaning to enable business managers take best profitable decisions. Through this paper such areas would be uncovered and an in-depth study would be done on business intelligence, structured and unstructured data, data warehouse, its architecture, data mining process, models, techniques and then discuss their potential applications, future and scope in huge enterprise databases that provides quick, predictive and summarized information to the decision makers and enables companies to
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