Management And Accounting Web

Data Mining and Big Data Bibliography

Provided by James R. Martin, Ph.D., CMA
Professor Emeritus, University of South Florida

Data Mining Main Page | Quantitative Methods Main Page

Barton, D. and D. Court. 2012. Making advanced analytics work for you: A Practical guide to capitalizing on big data. Harvard Business Review (October): 78-83. (Choose the right data, Build models that predict and optimize business outcomes, and Transform your company's capabilities).

Berinato, S. 2014. With big data comes big responsibility. Harvard Business Review (November): 100-104.

Berry, M. J. A. and G. S. Linoff. 2004. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management. Wiley Computer Publishing.

Bramer, M. 2007. Principles of Data Mining (Undergraduate Topics in Computer Science. Springer.

Brown-Liburd, H., H. Issa and D. Lombardi. 2015. Behavioral implications of big data's impact on audit judgment and decision making and future research directions. Accounting Horizons (June): 451-468.

Calderon, T. G., J. J. Cheh and I. Kim. 2003. How large corporations use data mining to create value. Management Accounting Quarterly (Winter): 1-11.

Cao, M., R. Chychyla and T. Stewart. 2015. Big data analytics in financial statement audits. Accounting Horizons (June): 423-429.

Davenport, T. H. 2006. Competing on analytics. Harvard Business Review (January): 98-107.

Davenport, T. H. 2014. What businesses can learn from sports analytics. MIT Sloan Management Review (Summer): 10-13.

Davenport, T. H. and J. G. Harris. 2007. Competing on Analytics: The New Science of Winning. Harvard Business School Press.

Davenport, T. H. and S. Kudyba. 2016. Designing and developing analytics-based data products. MIT Sloan Management Review (Fall): 82-89.

Davenport, T. H., J. G. Harris and Robert Morison. 2010. Analytics at Work: Smarter Decisions, Better Results. Harvard Business Press.

Davenport, T. H., P. Barth and R. Bean. 2012. How 'big data' is different. MIT Sloan Management Review (Fall): 43-46.

Debreceny, R. and G. L. Gray. 2004. Grab your picks and shovels! There's gold in your data. Strategic Finance (January): 24-28.

Dilla, W. N. and R. L. Raschke. 2015. Data visualization for fraud detection: Practice implications and a call for future research. International Journal of Accounting Information Systems (16): 1-22.

Fisher, I. E., M. R. Garnsey, S. Goel and K. Tam. 2010. The role of text analytics and information retrieval in the accounting domain. Journal of Emerging Technologies in Accounting (7): 1-24.

Fitzgerald, M. 2015. General Mills builds up big data to answer big questions. MIT Sloan Management Review (Summer): 34.

Fitzgerald, M. 2016. Better data brings a renewal at the Bank of England. MIT Sloan Management Review (Summer): 3-13.

Fitzgerald, M. 2016. Building a better car company with analytics. MIT Sloan Management Review (Summer): 40-44.

Fitzgerald, M. 2016. Data-driven city management. MIT Sloan Management Review (Summer): 3-10.

Fitzgerald, M. 2016. General Motors relies on IoT to keep its customers safe and secure. MIT Sloan Management Review (Summer): 86-91.

Fogarity, D. and P. C. Bell. 2014. Should you outsource analytics? MIT Sloan Management Review (Winter): 41-45.

Gray, G. L. and R. S. Debreceny. 2014. A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits. International Journal of Accounting Information Systems 15(4): 357-380.

Griffin, P. A. and A. M. Wright. 2015. Commentaries on big data's importance for accounting and auditing. Accounting Horizons (June): 377-379.

Hagel, J. 2013. Why accountants should own big data. Journal of Accountancy (November): 20-21. (Business intelligence).

Han, J. and M. Kamber. 2006. Data Mining Concepts and Techniques. Morgan Kaufmann Publishers.

Hastie, T., R. Tibshirani and J. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, second edition. Springer.

Hayashi, A. M. 2014. Thriving in a big data world. MIT Sloan Management Review (Winter): 35-39.

Hey, T. 2010. The next scientific revolution. Harvard Business Review (November): 56-63.

Hoffman, R. 2016. Using artificial intelligence to set information free. MIT Sloan Management Review (Fall): 1-15.

Hogarth, R. M. and E. Soyer. 2015. Using simulated experience to make sense of big data. MIT Sloan Management Review (Winter): 49-54.

Janert, P. K. 2010. Data Analysis with Open Source Tools. O'Reilly Media.

Jans, M., M. Alles and M. Vasarhelyi. 2013. The case for process mining in auditing: Sources of value added and areas of application. International Journal of Accounting Information Systems 14(1): 1-20.

Jernigan, S., S. Ransbotham and D. Kiron. 2016. Data sharing and analytics drive success with IoT. MIT Sloan Management Review (Fall): 1-17.

Kane, G. C. 2015. How digital transformation is making health care safer, faster and cheaper. MIT Sloan Management Review (Fall): 41-47.

Koch, R. 2015. Big data or big empathy? Strategic Finance (December): 62-63.

Kovalerchuk, B., E. Vityaev and R. Holtfreter. 2007. Correlation of complex evidence in forensic accounting using data mining. Journal of Forensic Accounting 8(1-2): 53-88.

Krahel, J. P. and W. R. Titera. 2015. Consequences of big data and formalization on accounting and auditing standards. Accounting Horizons (June): 409-422.

Larose, D. T. 2004. Discovering Knowledge in Data: An Introduction to Data Mining. Wiley-Interscience.

Lin, P. P. 2014. What CPAs need to know about big data. The CPA Journal (November): 50-55.

Liu, B. 2007 and 2010. Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer.

Liu, Y. and K. C. Moffitt. 2016. Text mining to uncover the intensity of SEC comment letters and its association with the probability of 10-K restatement. Journal of Emerging Technologies in Accounting (13): 85-94.

Loveman, G. 2003. Diamonds in the data mine. Harvard Business Review (May): 109-123.

Markov, Z. and D. T. Larose. 2007. Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage. Wiley-Interscience.

Martin, J. R. Not dated. What is data mining? Management And Accounting Web. http://maaw.info/DataMining.htm

Matignon, R. 2007. Data Mining Using SAS Enterprise Miner. Wiley-Interscience.

May, T. 2009. The New Know: Innovation Powered by Analytics. Wiley.

McAfee, A. and E. Brynjolfsson. 2012. Big data: The management revolution: Exploiting vast new flows of information can radically improve your company's performance. But first you'll have to change your decision-making culture. Harvard Business Review (October): 60-68.

McCue, C. 2007. Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis. Butterworth-Heinemann.

Milton, M. 2009. Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions. O'Reilly Media.

Moffit, K. C. and M. A. Vasarhelyi. 2013. Editorial. AIS in a age of big data. Journal of Information Systems (Fall): 1-19.

Nichols, W. 2013. Advertising analytics 2.0: Marketers now have and unprecedented ability to fine-tune their allocation decisions while making course corrections in real time. Harvard Business Review (March): 60-68.

Nisbet, R., J. Eder IV and G. Miner. 2009. Handbook of Statistical Analysis and Data Mining Applications. Academic Press.

Padmanabhan, B. and A. Tuzhilin. 2002. Knowledge refinement based on the discovery of unexpected patterns in data mining. Decision Support Systems 33(3): 309-321.

Padmanabhan, B. and A. Tuzhilin. 2003. On the use of optimization for data mining: Theoretical interactions and eCRM opportunities. Management Science (October): 1327-1343.

Peters, M. D., B. Wieder, S. G. Sutton and J. Wakefield. 2016. Business intelligence systems use in performance capabilities: Implications for enhanced competitive advantage. International Journal of Accounting Information Systems (21): 1-17.

Rajaraman, A., J. Leskovec and J. D. Ullman. 2012. Mining of Massive Datasets. (Link to Rajaraman, Leskovec and Ullman).

Redman, T. C. 2008. Data Driven: Profit from Your Most Important Business Asset. Harvard Business School Press.

Roberts-Witt, S. L. 2001. Gold diggers: Let customers and partners mine your data using new e-business intelligence tools. It could turn into a gold rush. PC Magazine (February, 20): ibiz 6-ibiz 10.

Roberts-Witt, S. L. 2002. Data mining: What lies beneath? Finding patterns in customer behavior can deliver profitable insights into your business. PC Magazine (November, 19): iBiz 1-6. (Note).

Rosenbaum, D. 2012. Digging out from big data: Unstructured data is piling up in corporate computers, making compliance and other tasks more difficult. CFO (July/August): 32-33.

Ross, J. W., C. M. Beath and A. Quaadgras. 2013. You may not need big data after all. Harvard Business Review (December): 90-98.

Schymik, G., K. Corral, D. Schuff and R. St. Louis. 2015. The benefits and costs of using metadata to improve enterprise document searches. Decision Sciences 46(6): 1049-1075.

Scott, J. 2015. Optimizing big data. Strategic Finance (November): 12.

Shirata, C. Y. and M. Sakagami. 2008. An analysis of the “going concern assumption”: Text mining from Japanese financial reports. Journal of Emerging Technologies in Accounting (5): 1-16.

Shirata, C. Y., H. Takeuchi, S. Ogino and H. Watanabe. 2011. Extracting key phrases as predictors of corporate bankruptcy: Empirical analysis of annual reports by text mining. Journal of Emerging Technologies in Accounting (8): 31-44.

Tan, P., M. Steinbach and V. Kumar. 2005. Introduction to Data Mining. Addison Wesley.

Torgo, L. 2010. Data Mining with R: Learning with Case Studies. Chapman and Hall/CRC.

Tsiptsis, K. and A. Chorianopoulos. 2010. Data Mining Techniques in CRM: Inside Customer Segmentation. Wiley.

Vasarhelyi, M. A., A. Kogan and B. M. Tuttle. 2015. Big data in accounting: An overview. Accounting Horizons (June): 381-396.

Wang, J. and J. G. S. Yang. 2009. Data mining techniques for auditing attest function and fraud detection. Journal of Forensic & Investigative Accounting 1(1): 1-24.

Warren, J. D. Jr., K. C. Moffitt and P. Byrnes. 2015. How big data will change accounting. Accounting Horizons (June): 397-407.

Williams, S. 2011. 5 Barriers to BI success and how to overcome them. Strategic Finance (July): 26-33. (Note).

Witten, I. H. and E. Frank. 1999. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufman.

Witten, I. H. and E. Frank. 2005. Data Mining: Practical Machine Learning Tools and Techniques, 2nd Edition. Morgan Kaufman.

Yoon, K., L. Hoogduin and L. Zhang. 2015. Big data as complementary audit evidence. Accounting Horizons (June): 431-438.

Zhang, J., X. Yang and D. Appelbaum. 2015. Toward effective big data analysis in continuous auditing. Accounting Horizons (June): 469-476.

Zheng, Z., B. Padmanabhan and S. Kimbrough. 2003. On the existence and significance of data preprocessing biases in web usage mining. INFORMS Journal on Computing 15(2): 148-170.