Bibliography for MN3515 Business Data Analytics BETA

Agrawal, R., Imieliński, T. and Swami, A. (1993) ‘Mining Association Rules Between Sets of Items in Large Databases’, ACM SIGMOD Record, 22(2), pp. 207–216. Available at: https://doi.org/10.1145/170035.170072.

Ashenfelter, O., Ashmore, D. and Lalonde, R. (no date) Bordeaux Wine Vintage Quality and the Weather. Available at: http://www.liquidasset.com/orley.htm.

Berlinger, E. et al. (2015) Mastering R for Quantitative Finance. Packt Publishing. Available at: https://www.safaribooksonline.com/library/view/mastering-r-for/9781783552078/.

Bertolucci, J. (2014) Data Scientists Want Big Data Ethics Standards | InformationWeek. Available at: http://www.informationweek.com/big-data/big-data-analytics/data-scientists-want-big-data-ethics-standards/d/d-id/1315798.

Best, J. (2013) IBM Watson: The Inside Story of How the Jeopardy-Winning Supercomputer Was Born, and What It Wants to Do Next | TechRepublic. Available at: http://www.techrepublic.com/article/ibm-watson-the-inside-story-of-how-the-jeopardy-winning-supercomputer-was-born-and-what-it-wants-to-do-next/.

de Bree, T. (no date) 8 Questions Every Business Analyst Should Ask | Modern Analyst. Available at: http://www.modernanalyst.com/Resources/Articles/tabid/115/ID/179/8-Questions-Every-Business-Analyst-Should-Ask.aspx.

Brynjolfsson, E. (2011) ‘Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?’, SSRN Electronic Journal [Preprint]. Available at: https://doi.org/10.2139/ssrn.1819486.

Buytendijk, F. and Heiser, J. (2013) ‘Confronting the Privacy and Ethical Risks of Big Data’, Financial Times [Preprint]. Available at: https://www.ft.com/content/105e30a4-2549-11e3-b349-00144feab7de.

Chapman, P. (2000) ‘CRISP-DM 1.0: Step-by-Step Data Mining Guide’. SPSS. Available at: https://the-modeling-agency.com/crisp-dm.pdf.

Cukier, K.N. and Mayer-Schoenberger, V. (2013) Why Big Data Is on the Rise | Foreign Affairs. Available at: https://www.foreignaffairs.com/articles/2013-04-03/rise-big-data.

Dallaway, E. (2015a) ‘Ten Data-Driven Sporting Victories - Part One | Technology’, The Guardian [Preprint]. Available at: http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-one.

Dallaway, E. (2015b) ‘Ten Data-Driven Sporting Victories - Part Two | Technology’, The Guardian [Preprint]. Available at: http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-two.

Daróczi, G. et al. (2013) Introduction to R for Quantitative Finance. Packt Publishing. Available at: https://www.safaribooksonline.com/library/view/introduction-to-r/9781783280933/.

Datasets for Data Mining and Data Science (no date). Available at: http://www.kdnuggets.com/datasets/index.html.

Davenport, T. (2007) ‘The Dark Side of Customer Analytics’, Harvard Business Review [Preprint]. Available at: http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=24635693&site=ehost-live.

DeAsi, G. (no date) How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google) | Pointillist. Available at: https://web.archive.org/web/20221020180045/https://www.pointillist.com/blog/customer-behavior-data/.

Decision Support Systems Resources | DSSResources (no date). Available at: http://dssresources.com/.

Deloitte and Ibm, We’re Facing a Huge Uk Digital Skills Gap - Infographic | Ignite (no date). Available at: https://www.ignite.digital/uk-digital-skills-gap-infographic/.

Egger, D. (no date) ‘Business Metrics for Data-Driven Companies: 20-Item Checklist | Onyx Reporting’. Available at: https://web.archive.org/web/20210119104435/http://www.onyxreporting.com/uploads/4/0/8/5/40851971/20itemchecklist.pdf.

Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P. (1996) ‘The KDD Process for Extracting Useful Knowledge From Volumes of Data (Knowledge Discovery in Databases)’, Communications of the ACM, 39(11), pp. 27–34. Available at: https://doi.org/10.1145/240455.240464.

Gerber, A.S., Green, D.P. and Larimer, C.W. (2008) ‘Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment’, The American Political Science Review, 102(1), pp. 33–48. Available at: https://www.jstor.org/stable/27644496.

Go, A., Bhayani, R. and Huang, L. (no date) ‘Twitter Sentiment Classification using Distant Supervision’. Available at: http://cs.stanford.edu/people/alecmgo/papers/TwitterDistantSupervision09.pdf.

Goldfarb, A. and Tucker, C.E. (2011) ‘Privacy Regulation and Online Advertising’, Management Science, 57(1), pp. 57–71. Available at: https://doi.org/10.1287/mnsc.1100.1246.

Goodwin, K. (2013) A Stakeholder Interview Checklist | Boxes and Arrows. Available at: http://boxesandarrows.com/a-stakeholder-interview-checklist/.

Grace-Martin, K. (no date) Seven Ways to Make up Data: Common Methods to Imputing Missing Data | The Analysis Factor. Available at: https://www.theanalysisfactor.com/seven-ways-to-make-up-data-common-methods-to-imputing-missing-data/.

Hahsler, M. et al. (no date) ‘Introduction to Arules – A Computational Environment for Mining Association Rules and Frequent Item Sets’. Available at: https://cran.r-project.org/web/packages/arules/vignettes/arules.pdf.

Hays, C.L. (2004) ‘What Wal-Mart Knows About Customers’ Habits’, The New York Times [Preprint]. Available at: http://www.nytimes.com/2004/11/14/business/yourmoney/what-walmart-knows-about-customers-habits.html?_r=1.

Hetherington, R. (2015) Preventing Customer Churn With Better Data Analytics. Available at: https://www.digitalistmag.com/industries/banking/2015/06/23/preventing-customer-churn-with-better-data-analytics-3-02974982.

How to Become a Data Scientist (Part 1/3) – Towards Data Science A Medium (no date). Available at: https://medium.com/towards-data-science/how-to-become-a-data-scientist-part-1-3-8706a62b809e?imm_mid=0f59d0&cmp=em-data-na-na-newsltr_20170823.

How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google) (no date). Available at: https://www.pointillist.com/blog/customer-behavior-data/.

How to Use read.csv() to Import Data in R (no date). Available at: http://www.dummies.com/programming/r/how-to-use-read-csv-to-import-data-in-r/.

Hype Cycle for Business Intelligence and Analytics, 2016 (no date). Available at: https://www.gartner.com/document/code/290879?ref=grbody&refval=3574217.

Hype Cycle for Data Science, 2016 (no date). Available at: https://www.gartner.com/document/code/303293?ref=grbody&refval=3574217.

IBM Big Data and Analytics - Case Studies - United Kingdom (2015). IBM Corporation. Available at: https://web.archive.org/web/20150221100253/http://www.ibm.com/big-data/uk/en/big-data-and-analytics/case-studies.html.

IBM Cognos Analytics on Cloud - United Kingdom (no date). Available at: https://web.archive.org/web/20210604092138/https://www.ibm.com/uk-en/products/cognos-analytics.

‘IBM’s Watson Computer Plays Jeopardy!!! | YouTube’ (2013). Available at: https://www.youtube.com/watch?v=P18EdAKuC1U.

ITScore for BI and Analytics (no date). Available at: https://www.gartner.com/document/code/314086?ref=grbody&refval=3574217.

Jain, D. and Gautam, S. (no date) ‘Implementation of Apriori Algorithm in Health Care Sector: A Survey’, International Journal of Computer Science and Communication Engineering, 2(4), pp. 26–32.

Jeet, P. and Vats, P. (2017) Learning Quantitative Finance with R. Packt Publishing. Available at: https://www.safaribooksonline.com/library/view/learning-quantitative-finance/9781786462411/.

Kenny, G. (2014) ‘Five Questions to Identify Key Stakeholders’, Harvard Business Review [Preprint]. Available at: https://hbr.org/2014/03/five-questions-to-identify-key-stakeholders.

Lee, L. and Pang, B. (no date) ‘Opinion Mining and Sentiment Analysis [open access]’, Foundations and Trends in Information Retrieval, 2(1–2), pp. 1–135. Available at: http://www.cs.cornell.edu/home/llee/omsa/omsa.pdf.

Lehmann, J. and Joseph, S. (2009) Biochar for Environmental Management: Science and Technology. London: Earthscan.

Lewis, M. (2004a) Moneyball: The Art of Winning an Unfair Game. New York, New York: W.W. Norton & Company.

Lewis, M. (2004b) Moneyball: The Art of Winning an Unfair Game. New York, New York: W.W. Norton & Company.

Manyika, J. et al. (2011) Big Data: The Next Frontier for Innovation, Competition, and Productivity | McKinsey & Company. Available at: https://web.archive.org/web/20200606014002/https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation.

Mason, H. (2010) A Taxonomy of Data Science | Dataists. Available at: https://web.archive.org/web/20210728133552/http://www.dataists.com/2010/09/a-taxonomy-of-data-science/.

Miller, B. (2011) ‘Moneyball’. Columbia Pictures.

Moro, S., Cortez, P. and Rita, P. (2014) ‘A Data-Driven Approach to Predict the Success of Bank Telemarketing’, Decision Support Systems, 62, pp. 22–31. Available at: https://doi.org/10.1016/j.dss.2014.03.001.

Pious, K. (2013) Interacting With Stakeholders as a Business Analyst: Who Are You Dealing With? | Captech Consulting. Available at: https://web.archive.org/web/20151015043859/https://www.captechconsulting.com/blogs/interacting-with-stakeholders-as-a-business-analyst-who-are-you-dealing-with.

Provost, F. and Fawcett, T. (2013a) Data Science for Business. Beijing: O’Reilly. Available at: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973.

Provost, F. and Fawcett, T. (2013b) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013c) Data Science for Business. Beijing: O’Reilly. Available at: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973.

Provost, F. and Fawcett, T. (2013d) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013e) Data Science for Business. Beijing: O’Reilly. Available at: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973.

Provost, F. and Fawcett, T. (2013f) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013g) Data Science for Business. Beijing: O’Reilly. Available at: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973.

Provost, F. and Fawcett, T. (2013h) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013i) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013j) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013k) Data Science for Business. Beijing: O’Reilly.

Provost, F. and Fawcett, T. (2013l) Data Science for Business. Beijing: O’Reilly.

Sharda, R. (2014a) Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson.

Sharda, R. (2014b) Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson.

Sharda, R., Delen, D. and Turban, E. (2014) Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson.

Sharma, A.S. (2013) Stakeholder Analysis and Management | ExpertBA. Available at: https://web.archive.org/web/20161028033209/http://expertbusinessanalyst.com/stakeholder-analysis-and-management/.

Sherman, R. (2014) Business Intelligence Guidebook: From Data Integration to Analytics. Amsterdam: Morgan Kaufmann.

Sherman, R. (2015) Business Intelligence Guidebook: From Data Integration to Analytics. Amsterdam: Elsevier/Morgan Kaufmann. Available at: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1832704.

SIGKDD (no date). Available at: http://kdd.org/.

TDWI | Advancing All Things Data | Business Intelligence, Data Warehousing, Analytics | Education & Research (no date). Available at: https://tdwi.org/Home.aspx.

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The Case for Data Ethics | Accenture Outlook (no date). Available at: https://www.accenture.com/gb-en/insight-outlook-case-data-ethics.

Top 10 Strategic Technology Trends for 2017: Artificial Intelligence and Advanced Machine Learning (no date). Available at: https://www.gartner.com/document/code/319573?ref=grbody&refval=3645332.

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‘Watson and the Jeopardy! Challenge’ (2014). Available at: https://www.youtube.com/watch?v=_Xcmh1LQB9I.

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Welcome! | Score a Hit! (no date). Available at: https://web.archive.org/web/20160704080559/http://www.scoreahit.com/.

Wick, A. (2012) Six Effective Elicitation Questions to Ask Your Stakeholders | BA Times. Available at: http://www.batimes.com/articles/six-effective-elicitation-questions-to-ask-your-stakeholders.html.

Zhang, C. and Zhang, S. (no date) Association Rule Mining. Springer Berlin Heidelberg.

Zumel, N. and Mount, J. (2014a) Practical Data Science With R. Shelter Island, NY: Manning. Available at: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar.

Zumel, N. and Mount, J. (2014b) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014c) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014d) Practical Data Science With R. Shelter Island, NY: Manning. Available at: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar.

Zumel, N. and Mount, J. (2014e) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014f) Practical Data Science With R. Shelter Island, NY: Manning. Available at: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar.

Zumel, N. and Mount, J. (2014g) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014h) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014i) Practical Data Science With R. Shelter Island, New York: Manning Publications Co.

Zumel, N. and Mount, J. (2014j) Practical Data Science With R. Shelter Island, NY: Manning Publications Co.

Zumel, N. and Mount, J. (2014k) Practical Data Science With R. Shelter Island, New York: Manning Publications Co.