BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS, TECHNIQUES AND BENEFITS

For companies maintaining direct contact with large numbers of customers, however, a growing number channel-oriented applications (e.g. e-commerce support, call center support) create a new data management challenge: that is effective way of integrating enterprise applications in real time. To learn from the past and forecast the future, many companies are adopting Business Intelligence (BI) tools and systems. Companies have understood the importance of enforcing achievements of the goals defined by their business strategies through business intelligence concepts. It describes the insights on the role and requirement of real time BI by examining the business needs. 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.

[1]  K. Srikantaiah,et al.  From Information Management to Knowledge Management : Beyond the ' Hi-Tech Hidebound ' Systems , 1996 .

[2]  Rama Chellappa,et al.  Identification of humans using gait , 2004, IEEE Transactions on Image Processing.

[3]  Josef Schiefer,et al.  Enhanced business intelligence - supporting business processes with real-time business analytics , 2005, 16th International Workshop on Database and Expert Systems Applications (DEXA'05).

[4]  Michael Goh Kah Ong,et al.  A single-sensor hand geometry and palmprint verification system , 2003, WBMA '03.

[5]  D. Batra,et al.  Gabor filter based fingerprint classification using support vector machines , 2004, Proceedings of the IEEE INDICON 2004. First India Annual Conference, 2004..

[6]  Saeid Fazli,et al.  Gait Recognition using SVM and LDA , 2011 .

[7]  W. H. Inmon,et al.  Building the Operational Data Store , 1995 .

[8]  Sung-Hyuk Cha,et al.  Evaluation of Biometric Identification in Open Systems , 2005, AVBPA.

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

[10]  Mark S. Nixon,et al.  Extended Model-Based Automatic Gait Recognition of Walking and Running , 2001, AVBPA.

[11]  Thomas Serre,et al.  Hierarchical classification and feature reduction for fast face detection with support vector machines , 2003, Pattern Recognit..

[12]  Kohei Arai,et al.  Human Gait Gender Classification using 2D Discrete Wavelet Transforms Energy , 2011 .

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

[14]  Dibo Hou,et al.  A Novel Lane Detection Algorithm Based on Support Vector Machine , 2005 .

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

[16]  Milena Tvrdíková.  Support of Decision Making by Business Intelligence Tools , 2007, 6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07).

[17]  Prabin Kumar Bora,et al.  Trajectory Guided Recognition of Hand Gestures having only Global Motions , 2008 .

[18]  Leif H. Finkel,et al.  Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition , 2006, J. Multim..

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

[20]  Davrondzhon Gafurov,et al.  A Survey of Biometric Gait Recognition: Approaches, Security and Challenges , 2007 .

[21]  G. Gangadharan,et al.  Business intelligence systems: design and implementation strategies , 2004, 26th International Conference on Information Technology Interfaces, 2004..

[22]  A Min Tjoa,et al.  Sense & response service architecture (SARESA): an approach towards a real-time business intelligence solution and its use for a fraud detection application , 2005, DOLAP '05.

[23]  Yogesh Malhotra,et al.  From Information Management to Knowledge Management: Beyond the "Hi-Tech Hidebound" Systems , 2001 .

[24]  R. Bhavani,et al.  Biometric Authorization System using Gait Biometry , 2011, ArXiv.

[25]  James J. Little,et al.  Biometric Gait Recognition , 2003, Advanced Studies in Biometrics.

[26]  Alex Berson,et al.  Building Data Mining Applications for CRM , 1999 .

[27]  Thomas H. Davenport,et al.  Process Innovation: Reengineering Work Through Information Technology , 1992 .

[28]  Le Gruenwald,et al.  A survey of data mining and knowledge discovery software tools , 1999, SKDD.