BUSINESS INTELLIGENCE: AN INTEGRATED APPROACH

Business intelligence systems combine operational and historical data with analytical tools to present valuable and competitive information to business planners and decision makers. The objective of Business intelligence (BI) is to improve the timeliness and quality of information, and enable managers to be able to better understand the position of their firm as in comparison to competitors. Business intelligence applications and technologies can help companies to analyze changing trends in market share; changes in customer behavior and spending patterns; customers’ preferences; company capabilities; and market conditions. Business intelligence can be used to help analysts and managers determine which adjustments are most likely to respond to changing trends. The emergence of the data warehouse as a repository, advances in data cleansing, increased capabilities of hardware and software, and the emergence of the web architecture all combine to create a richer business intelligence environment than was available previously. In this paper, an attempt has been made to present a framework for building a BI system. While the business world is rapidly changing and the business processes are becoming more and more complex making it more difficult for managers to have comprehensive understanding of business environment. The factors of globalization, deregulation, mergers and acquisitions, competition and technological innovation, have forced companies to re-think their business strategies and many large companies have resorted to Business Intelligence (BI) techniques to help them understand and control business processes to gain competitive advantage. BI is primarily used to improve the timeliness and quality of information, and enable managers better understand the position of their firm as in comparison to competitors. BI applications and technologies help companies to analyze changing trends in market share; changes in customer behavior and spending patterns; customers' preferences; company capabilities; and market conditions. It is used to help analysts and managers determine which adjustments are most likely to respond to changing trends. It has emerged as a concept for analyzing collected data with the purpose to help decision making units get a better comprehensive knowledge of an organization’s operations, and thereby make better business decisions. BI is an area of Decision Support System (DSS) that which is an information system that can be used to support complex decision making, and solving complex, semi-structured, or ill-structured problems (Azevedo &

[1]  Hans Peter Luhn,et al.  A Business Intelligence System , 1958, IBM J. Res. Dev..

[2]  Gregory Piatetsky-Shapiro,et al.  Knowledge Discovery in Databases: An Overview , 1992, AI Mag..

[3]  W. H. Inmon,et al.  Building the data warehouse , 1992 .

[4]  Arno Siebes,et al.  Data Mining: the search for knowledge in databases. , 1994 .

[5]  Michael J. Corey,et al.  Oracle data warehousing , 1996 .

[6]  Ralph Kimball,et al.  The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses , 1996 .

[7]  W. H. Inmon,et al.  Building the data warehouse (2nd ed.) , 1996 .

[8]  Daniel L. Sherrell,et al.  Communications of the Association for Information Systems , 1999 .

[9]  Mark Hammond,et al.  e-Business Intelligence: Turning Information into Knowledge into Profit , 2000 .

[10]  Efraim Turban,et al.  Information Technology for Management: Making Connections for Strategic Advantage , 2000 .

[11]  Stephan Kudyba,et al.  Data Mining and Business Intelligence: A Guide to Productivity , 2001 .

[12]  Robert Thierauf,et al.  Effective Business Intelligence Systems , 2001 .

[13]  Christer Carlsson,et al.  Past, present, and future of decision support technology , 2002, Decis. Support Syst..

[14]  Lakshmi S. Iyer,et al.  Knowledge warehouse: an architectural integration of knowledge management, decision support, artificial intelligence and data warehousing , 2002, Decis. Support Syst..

[15]  Larissa Terpeluk Moss,et al.  Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications , 2003 .

[16]  M. Jarke,et al.  Fundamentals of Data Warehouses , 2003, Springer Berlin Heidelberg.

[17]  Matteo Golfarelli,et al.  Beyond data warehousing: what's next in business intelligence? , 2004, DOLAP '04.

[18]  M. Raisinghani.  Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks , 2004 .

[19]  Zhongzhi Shi,et al.  Techniques, Process, and Enterprise Solutions of Business Intelligence , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[20]  Robert Stackowiak,et al.  Oracle Data Warehousing and Business Intelligence Solutions , 2007 .

[21]  Zhan Cui,et al.  Benefits of Ontologies in Real Time Data Access , 2007, 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference.

[22]  Thomas D. Clark,et al.  The Dynamic Structure of Management Support Systems: Theory Development, Research Focus, and Direction , 2007, MIS Q..

[23]  Claudio Bartolini,et al.  A Service-oriented Architecture for Business Intelligence , 2007, IEEE International Conference on Service-Oriented Computing and Applications (SOCA '07).

[24]  Efraim Turban,et al.  Business Intelligence: Second European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures , 2013 .

[25]  Graham Pervan,et al.  Eight key issues for the decision support systems discipline , 2008, Decis. Support Syst..

[26]  Zbigniew Michalewicz,et al.  Adaptive Business Intelligence , 2009, Encyclopedia of Artificial Intelligence.

[27]  Manuel Filipe Santos,et al.  Business Intelligence - State of the Art, Trends, and Open Issues , 2018, KMIS.

[28]  Bill Hostmann,et al.  Magic Quadrant for Business Intelligence Platforms , 2012 .

[29]  Solomon Negash.  Business Intelligence , 2011, Lecture Notes in Business Information Processing.

[30]  David R. Firth,et al.  Communications of the Association for Information Systems , 2011 .