Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
article

Business intelligence and analytics: from big data to big impact

Published: 01 December 2012 Publication History

Abstract

Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.

References

[1]
Adomavicius, G., and Tuzhilin, A. 2005. "Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions," IEEE Transactions on Knowledge and Data Engineering (17:6), pp. 734-749.
[2]
Anderson, C. 2004. "The Long Tail," WIRED Magazine (12:10) (http://www.wired.com/wired/archive/12.10/tail.html).
[3]
Associated Press. 2012. "Columbia U Plans New Institute for Data Sciences," July 30 (http://www.cbsnews.com/8301-505245_162- 57482466/columbia-u-plans-new-institute-for-data-sciences/, accessed August 3, 2012).
[4]
Barabási, A. 2003. Linked: How Everything Is Connected to Everything Else and What it Means for Business, Science, and Everyday Life, New York: Plume.
[5]
Batagelj, V., and Mrvar, A. 1998. "Pajek: A Program for Large Network Analysis," Connections (21), pp. 47-57.
[6]
Bettencourt, L. M.A., Cintrón-Arias, A., Kaiser, D. I., and Castillo-Chávez, C. 2006. "The Power of a Good Idea: Quantitative Modeling of the Spread of Ideas from Epidemiological Models," Physica A (364), pp. 513-536.
[7]
Bitterer, A. 2011. "Hype Cycle for Business Intelligence," Gartner, Inc., Stamford, CT.
[8]
Blei, D. M. 2012. "Probabilistic Topic Models," Communications of the ACM (55:4), pp. 77-84.
[9]
Bloomberg Businessweek. 2011. "The Current State of Business Analytics: Where Do We Go from Here?," Bloomberg Business-week Research Services (http://www.sas.com/resources/asset/ busanalyticsstudy_wp_08232011.pdf).
[10]
Borgatti, S. P., Everett, M. G., and Freeman, L. C. 2002. UCInet for Windows: Software for Social Network Analysis, Harvard, MA: Analytic Technologies.
[11]
Brantingham, P. L. 2011. "Computational Criminology," Keynote Address to the European Intelligence and Security Informatics Conference, Athens, Greece, September 12-14.
[12]
Brin, S., and Page, L. 1998. "The Anatomy of a Large-Scale Hypertextual Web Search Engine," Computer Network and ISDN Systems (30), pp. 107-117.
[13]
Brumfiel, G. 2911, "High-Energy Physics: Down the Petabyte Highway," Nature (469), pp. 282-283.
[14]
Chaudhuri, S., Dayal, U., and Narasayya, V. 2011. "An Overview of Business Intelligence Technology," Communications of the ACM (54:8), pp. 88-98.
[15]
Chen, H. 2006. Intelligence and Security Informatics for International Security: Information Sharing and Data Mining, New York: Springer.
[16]
Chen, H. 2009. "AI, E-Government, and Politics 2.0," IEEE Intelligent Systems (24:5), pp. 64-67.
[17]
Chen, H. 2011a. "Design Science, Grand Challenges, and Societal Impacts," ACM Transactions on Management Information Systems (2:1), pp. 1:1-1:10.
[18]
Chen, H. 2011b. "Smart Health and Wellbeing," IEEE Intelligent Systems (26:5), pp. 78-79.
[19]
Chen, H. 2012. Dark Web: Exploring and Mining the Dark Side of the Web, New york: Springer.
[20]
Chen, H., Brandt, L., Gregg, V., Traunmuller, R., McIntosh, A., Dawes, S., Hovy, E., and Larson, C. A. (eds.). 2007. Digital Government: E-Government Research, Case Studies, and Implementation, New York: Springer.
[21]
Chen, H., Reid, E., Sinai, J., Silke, A., and Ganor, B. (eds.). 2008. Terrorism Informatics: Knowledge Management and Data Mining for Homeland Security, New York: Springer.
[22]
Chiang, R. H. L., Goes, P., and Stohr, E. A. 2012. "Business Intelligence and Analytics Education and Program Development: A Unique Opportunity for the Information Systems Discipline," ACM Transactions on Management Information Systems (3:3), forthcoming.
[23]
Davenport, T. H. 2006. "Competing on Analytics," Harvard Business Review (84:1), p. 98-107.
[24]
Doan, A., Ramakrishnan, R., and Halevy, A. Y. 2011. "Crowd-sourcing Systems on the World-Wide Web," Communications of the ACM (54:4), pp. 86-96.
[25]
Fortunato, S. 2010. "Community Detection in Graphs," Physics Reports (486:3-5), pp. 75-174.
[26]
Frank, O., and Strauss, D. 1986. "Markov Graphs," Journal of the American Statistical Association (81:395), pp. 832-842.
[27]
Freeman, T. 2005. The World is Flat: A Brief History of the Twenty-First Century, New York: Farrar, Straus, and Giroux.
[28]
Gelfand, A. 2011/2012. "Privacy and Biomedical Research: Building a Trust Infrastructure--An Exploration of Data-Driven and Process-Driven Approaches to Data Privacy," Biomedical Computation Review, Winter, pp. 23-28 (available at http://biomedicalcomputationreview.org/content/privacy-and-biomedical-research-building-trust-infrastructure, accessed August 2, 2012).
[29]
Hanauer, D. A., Rhodes, D. R., and Chinnaiyan, A. M. 2009. "Exploring Clinical Associations Using '-Omics' Based Enrichment Analyses," PLoS ONE (4:4): e5203.
[30]
Hanauer, D. A., Zheng, K., Ramakrishnan, N., and Keller, B. J. 2011. "Opportunities and Challenges in Association and Episode Discovery from Electronic Health Records," IEEE Intelligent Systems (26:5), pp. 83-87.
[31]
Henschen, D. 2011. "Why All the Hadoopla?" Information Week, November 14, pp. 19-26.
[32]
Hevner, A., March, S. T., Park, J., and Ram. S. 2004. "Design Science Research in Information Systems," MIS Quarterly (28:1), pp. 75-105.
[33]
Hirsch, J. E. 2005. "An Index to Quantify an Individual's Scientific Research Output," Proceedings of the National Academy of Sciences of the United States of America (102:46), pp. 16569-16572.
[34]
Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M., and Morris, M. 2008. "ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Network," Journal of Statistical Software (24:3) (http://www.ncbi.nlm.nih.gov/ pmc/articles/PMC2743438/).
[35]
IBM. 2011. "The 2011 IBM Tech Trends Report: The Clouds are Rolling In...Is Your Business Ready?," November 15 (http://www.ibm.com/developerworks/techntrendsreport; accessed August 4, 2012).
[36]
Karpf, D. 2009. "Blogsphere Research: A Mixed-Methods Approach to Rapidly Changing Systems," IEEE Intelligent Systems (24:5), pp. 67-70.
[37]
Liben-Nowell, D., and Kleinberg, J. 20007. "The Link-Prediction Problem for Social Networks," Journal of American Society for Information Science and Technology (58:7), pp. 1019-1031.
[38]
Lin, Y., Brown, R. A., Yang, H. J., Li, S., Lu, H., and Chen, H. 2011. "Data Mining Large-Scale Electronic Health Records for Clinical Support," IEEE Intelligent Systems (26:5), pp. 87-90.
[39]
Lusch, R. F., Liu, Y., and Chen, Y. 2010. "The Phase Transition of Markets and Organizations: The New Intelligence and Entrepreneurial Frontier," IEEE Intelligent Systems (25:1), pp. 71-75.
[40]
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., and Byers, A. H. 2011. "Big Data: The Next Frontier for Innovation, Competition, and Productivity," McKinsey Global Institute (http://www.mckinsey.com/insights/mgi/research/ technology_and_innovation/big_data_the_next_frontier_for_in novation; accessed August 4, 2012).
[41]
Manning, C. D., and Schütze, H. 1999. Foundations of Statistical Natural Language Processing, Cambridge, MA: The MIT Press.
[42]
March, S. T., and Storey, V. C. 2008. "Design Science in the Information Systems Discipline," MIS Quarterly (32:4), pp. 725-730.
[43]
Maybury, M. T. (ed.). 2004. New Directions in Question Answering, Cambridge, MA: The MIT Press.
[44]
McCallum, A. 2002. "Mallet: A Machine Learning for Language Toolkit," University of Massachusetts, Amherst (http://mallet.cs.umass.edu/).
[45]
Miller, K. 2012a. "Big Data Analytics in Biomedical Research," Biomedical Computation Review (available at http:// biomedicalcomputationreview.org/content/big-data-analytics-biomedical-research; accessed August 2, 2012).
[46]
Miller, K. 2012b. "Leveraging Social Media for Biomedical Research: How Social Media Sites Are Rapidly Doing Unique Research on Large Cohorts," Biomedical Computation Review (available at http://biomedicalcomputationreview.org/content/ leveraging-social-media-biomedical-research; accessed August 2, 2012).
[47]
National Research Council. 2008. Behavioral Modeling and Simulation: From Individuals to Societies, Committee on Organizational Modeling: From Individuals to Societies, G. L. Zacharias, J. MacMillan and S. B. Van Hemel (eds.), Board on Behavioral, Cognitive, and Sensory Sciences, Division of Behavioral and Social Sciences and Education, Washington, DC: The National Academies Press.
[48]
O'Reilly, T. 2005. "What Is Web 2.0? Design Patterns and Business Models for the Next Generation of Software," September 30, (http://www.oreillynet.com/pub/a/oreilly/tim/ news/2005/09/30/what-is-web-20.html).
[49]
Pang, B., and Lee, L. 2008. "Opinion Mining and Sentiment Analysis," Foundations and Trends in Information Retrieval (2:1-2), pp. 1-135.
[50]
Patterson, D. A. 2008. "Technical Perspective: The Data Center Is the Computer," Communications of the ACM (51:1), p. 105.
[51]
Perlroth, N., and Rusli, E. M. 2012. "Security Start-Ups Catch Fancy of Investors," New York Times, Technology Section, August 5.
[52]
Robins, G., Pattison, P., Kalish, Y., and Lusher, D. 2007. "An Introduction to Exponential Random Graph (p*) Models for Social Networks," Social Networks (29:2), pp. 173-191.
[53]
Russom, P. 2011. "Big Data Analytics," TDWI Best Practices Report, Fourth Quarter.
[54]
Sallam, R. L., Richardson, J., Hagerty, J., and Hostmann, B. 2011. "Magic Quadrant for Business Intelligence Platforms," Gartner Group, Stamford, CT.
[55]
Salton, G. 1989. Automatic Text Processing, Reading, MA: Addison Wesley.
[56]
Schonfeld, E. 2005. "The Great Giveaway," Business 2.0 (6:3), pp. 80-86.
[57]
Snider, M. 2012. "More Businesses Getting Their Game On," USA Today, July 30.
[58]
Stonebraker, M., Abadi, D., DeWitt, D. J., Madden, S., Pavlo, A., and Rasin, A. 2012. "MapReduce and Parallel DBMSs: Friends or Foes," Communications of the ACM (53:1), pp. 64-71.
[59]
The Economist. 2010a. "The Data Deluge," Special Report on Managing Information, Technology Section, February 25 (http://www.economist.com/node/15579717).
[60]
The Economist. 2010b. "All Too Much," Special Report on Managing Information, Technology Section, February 25 (http://www.economist.com/node/15557421).
[61]
The Economist. 2011. "Beyond the PC," Special Report on Personal Technology, October 8 (http://www.economist.com/ node/21531109).
[62]
Turban, E., Sharda, R., Aronson, J. E., and King, D. 2008. Business Intelligence: A Managerial Approach, Boston: Pearson Prentice Hall.
[63]
U.S. Office of Homeland Security. 2002. National Strategy for Homeland Security, Washington, DC: Office of Homeland Security.
[64]
van der Aalst, W. 2012. "Process Mining: Overview and Opportunities," ACM Transactions on Management Information Systems (3:2), pp. 7:1-7:17.
[65]
Wactlar, H., Pavel, M., and Barkis, W. 2011. "Can Computer Science Save Healthcare?" IEEE Intelligent Systems (26:5), pp. 79-83.
[66]
Watson, H. J., and Wixom, B. H. 2007. "The Current State of Business Intelligence," IEEE Computer (40:9), pp. 96-99.
[67]
Watts, D. 2003. Six Degrees: The Science of a Connected Age, New York: W. W. Norton.
[68]
Witten, I. H., Frank, E., and Hall, M. 2011. Data Mining: Practical Machine Learning Tools and Techniques (3rd ed.), San Francisco: Morgan Kaufmann.
[69]
Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P.S., Zhou, Z.-H., Steinbach, M., Hand, D. J., and Steinberg, D. 2007. "Top 10 Algorithms in Data Mining," Knowledge and Information Systems (14:1), pp. 1-37.
[70]
Yang, H., and Callan, J. 2009. "OntoCop: Constructing Ontologies for Public Comments," IEEE Intelligent Systems (24:5), pp. 70-75.

Cited By

View all
  1. Business intelligence and analytics: from big data to big impact

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image MIS Quarterly
    MIS Quarterly  Volume 36, Issue 4
    December 2012
    331 pages

    Publisher

    Society for Information Management and The Management Information Systems Research Center

    United States

    Publication History

    Published: 01 December 2012

    Author Tags

    1. big data analytics
    2. business intelligence and analytics
    3. web 2.0

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 08 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Studying the cognitive relatedness between topics in the global science landscapeJournal of Information Science10.1177/0165551522112197050:6(1429-1448)Online publication date: 1-Dec-2024
    • (2023)Handling Missing Values in Information Systems ResearchInformation Systems Research10.1287/isre.2022.110434:1(5-26)Online publication date: 1-Mar-2023
    • (2023)Less Fragmented but Highly CentralizedSocial Science Computer Review10.1177/0894439321105811241:3(946-966)Online publication date: 1-Jun-2023
    • (2023)Boosting innovation performance through big data analyticsJournal of Information Science10.1177/0165551521104742549:5(1293-1308)Online publication date: 1-Oct-2023
    • (2023)Enterprise resource planning adoption model for well-informed decision in higher learning institutionsJournal of Information Science10.1177/0165551521101970349:3(792-813)Online publication date: 1-Jun-2023
    • (2023)Big Data-Driven Portfolio Simplification: Leveraging Self-Labeled Clustering to Enhance Decision-MakingProceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies10.1145/3632366.3632394(1-6)Online publication date: 4-Dec-2023
    • (2023)Research on Text Mining of JD Commodity Review Information Based on NLPProceedings of the 7th International Conference on Computer Science and Application Engineering10.1145/3627915.3628089(1-6)Online publication date: 17-Oct-2023
    • (2023)Data Analytics Insight-Driven Organizational AgilityProceedings of the 10th Multidisciplinary International Social Networks Conference10.1145/3624875.3624885(55-62)Online publication date: 4-Sep-2023
    • (2023)A Human-in-the-Loop Segmented Mixed-Effects Modeling Method for Analyzing Wearables DataACM Transactions on Management Information Systems10.1145/356427614:2(1-17)Online publication date: 25-Jan-2023
    • (2023)QAAS: quick accurate auto-scaling for streaming processingFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-022-1706-418:1Online publication date: 12-Aug-2023
    • Show More Cited By

    View Options

    View options

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media