Agrawal, Rakesh, Tomasz Imieliński, and Arun Swami, ‘Mining Association Rules Between Sets of Items in Large Databases’, ACM SIGMOD Record, 22.2 (1993), 207–16 <https://doi.org/10.1145/170035.170072>
Ashenfelter, Orley, David Ashmore, and Robert Lalonde, ‘Bordeaux Wine Vintage Quality and the Weather’ <http://www.liquidasset.com/orley.htm>
Berlinger, Edina, Ferenc Illés, Milán Badics, Ádám Banai, Gergely Daróczi, Barbara Dömötör, and others, Mastering R for Quantitative Finance (Packt Publishing, 2015) <https://www.safaribooksonline.com/library/view/mastering-r-for/9781783552078/>
Bertolucci, Jeff, ‘Data Scientists Want Big Data Ethics Standards | InformationWeek’, 2014 <http://www.informationweek.com/big-data/big-data-analytics/data-scientists-want-big-data-ethics-standards/d/d-id/1315798>
Best, Jo, ‘IBM Watson: The Inside Story of How the Jeopardy-Winning Supercomputer Was Born, and What It Wants to Do Next | TechRepublic’, 2013 <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, Tony, ‘8 Questions Every Business Analyst Should Ask | Modern Analyst’ <http://www.modernanalyst.com/Resources/Articles/tabid/115/ID/179/8-Questions-Every-Business-Analyst-Should-Ask.aspx>
Brynjolfsson, Erik, ‘Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?’, SSRN Electronic Journal, 2011 <https://doi.org/10.2139/ssrn.1819486>
Buytendijk, Frank, and Jay Heiser, ‘Confronting the Privacy and Ethical Risks of Big Data’, Financial Times, 2013 <https://www.ft.com/content/105e30a4-2549-11e3-b349-00144feab7de>
Chapman, Pete, ‘CRISP-DM 1.0: Step-by-Step Data Mining Guide’ (SPSS, 2000) <https://the-modeling-agency.com/crisp-dm.pdf>
Cukier, Kenneth Neil, and Viktor Mayer-Schoenberger, ‘Why Big Data Is on the Rise | Foreign Affairs’, 2013 <https://www.foreignaffairs.com/articles/2013-04-03/rise-big-data>
Dallaway, Eleanor, ‘Ten Data-Driven Sporting Victories - Part One | Technology’, The Guardian, 2015 <http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-one>
———, ‘Ten Data-Driven Sporting Victories - Part Two | Technology’, The Guardian, 2015 <http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-two>
Daróczi, Gergely, Agnes Vidovics-Dancs, Daniel Havran, Edina Berlinger, Márton Michaletzky, Michael Puhle, and others, Introduction to R for Quantitative Finance (Packt Publishing, 2013) <https://www.safaribooksonline.com/library/view/introduction-to-r/9781783280933/>
‘Datasets for Data Mining and Data Science’ <http://www.kdnuggets.com/datasets/index.html>
Davenport, Thomas, ‘The Dark Side of Customer Analytics’, Harvard Business Review, 2007 <http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=24635693&site=ehost-live>
DeAsi, Gary, ‘How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google) | Pointillist’ <https://web.archive.org/web/20221020180045/https://www.pointillist.com/blog/customer-behavior-data/>
‘Decision Support Systems Resources | DSSResources’ <http://dssresources.com/>
‘Deloitte and Ibm, We’re Facing a Huge Uk Digital Skills Gap - Infographic | Ignite’ <https://www.ignite.digital/uk-digital-skills-gap-infographic/>
Egger, Daniel, ‘Business Metrics for Data-Driven Companies: 20-Item Checklist | Onyx Reporting’ <https://web.archive.org/web/20210119104435/http://www.onyxreporting.com/uploads/4/0/8/5/40851971/20itemchecklist.pdf>
Fayyad, Usama, Gregory Piatetsky-Shapiro, and Padhraic Smyth, ‘The KDD Process for Extracting Useful Knowledge From Volumes of Data (Knowledge Discovery in Databases)’, Communications of the ACM, 39.11 (1996), 27–34 <https://doi.org/10.1145/240455.240464>
Gerber, Alan S., Donald P. Green, and Christopher W. Larimer, ‘Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment’, The American Political Science Review, 102.1 (2008), 33–48 <https://www.jstor.org/stable/27644496>
Go, Alec, Richa Bhayani, and Lei Huang, ‘Twitter Sentiment Classification Using Distant Supervision’ <http://cs.stanford.edu/people/alecmgo/papers/TwitterDistantSupervision09.pdf>
Goldfarb, Avi, and Catherine E. Tucker, ‘Privacy Regulation and Online Advertising’, Management Science, 57.1 (2011), 57–71 <https://doi.org/10.1287/mnsc.1100.1246>
Goodwin, Kim, ‘A Stakeholder Interview Checklist | Boxes and Arrows’, 2013 <http://boxesandarrows.com/a-stakeholder-interview-checklist/>
Grace-Martin, Karen, ‘Seven Ways to Make up Data: Common Methods to Imputing Missing Data | The Analysis Factor’ <https://www.theanalysisfactor.com/seven-ways-to-make-up-data-common-methods-to-imputing-missing-data/>
Hahsler, Michael, Bettina Grun, Kurt Hornik, and Christian Buchta, ‘Introduction to Arules – A Computational Environment for Mining Association Rules and Frequent Item Sets’ <https://cran.r-project.org/web/packages/arules/vignettes/arules.pdf>
Hays, Constance L., ‘What Wal-Mart Knows About Customers’ Habits’, The New York Times, 2004 <http://www.nytimes.com/2004/11/14/business/yourmoney/what-walmart-knows-about-customers-habits.html?_r=1>
Hetherington, Rob, ‘Preventing Customer Churn With Better Data Analytics’, 2015 <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’ <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)’ <https://www.pointillist.com/blog/customer-behavior-data/>
‘How to Use Read.Csv() to Import Data in R’ <http://www.dummies.com/programming/r/how-to-use-read-csv-to-import-data-in-r/>
‘Hype Cycle for Business Intelligence and Analytics, 2016’ <https://www.gartner.com/document/code/290879?ref=grbody&refval=3574217>
‘Hype Cycle for Data Science, 2016’ <https://www.gartner.com/document/code/303293?ref=grbody&refval=3574217>
‘IBM Big Data and Analytics - Case Studies - United Kingdom’ (IBM Corporation, 2015) <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’ <https://web.archive.org/web/20210604092138/https://www.ibm.com/uk-en/products/cognos-analytics>
‘IBM’s Watson Computer Plays Jeopardy!!! | YouTube’, 2013 <https://www.youtube.com/watch?v=P18EdAKuC1U>
‘ITScore for BI and Analytics’ <https://www.gartner.com/document/code/314086?ref=grbody&refval=3574217>
Jain, Divya, and Sumanlata Gautam, ‘Implementation of Apriori Algorithm in Health Care Sector: A Survey’, International Journal of Computer Science and Communication Engineering, 2.4, 26–32
Jeet, Param, and Prashant Vats, Learning Quantitative Finance with R (Packt Publishing, 2017) <https://www.safaribooksonline.com/library/view/learning-quantitative-finance/9781786462411/>
Kenny, Graham, ‘Five Questions to Identify Key Stakeholders’, Harvard Business Review, 2014 <https://hbr.org/2014/03/five-questions-to-identify-key-stakeholders>
Lee, Lillian, and Bo Pang, ‘Opinion Mining and Sentiment Analysis [Open Access]’, Foundations and Trends in Information Retrieval, 2.1–2, 1–135 <http://www.cs.cornell.edu/home/llee/omsa/omsa.pdf>
Lehmann, Johannes, and Stephen Joseph, Biochar for Environmental Management: Science and Technology (London: Earthscan, 2009)
Lewis, Michael, Moneyball: The Art of Winning an Unfair Game (New York, New York: W.W. Norton & Company, 2004)
———, Moneyball: The Art of Winning an Unfair Game (New York, New York: W.W. Norton & Company, 2004)
Manyika, James, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and others, ‘Big Data: The Next Frontier for Innovation, Competition, and Productivity | McKinsey & Company’, 2011 <https://web.archive.org/web/20200606014002/https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation>
Mason, Hilary, ‘A Taxonomy of Data Science | Dataists’, 2010 <https://web.archive.org/web/20210728133552/http://www.dataists.com/2010/09/a-taxonomy-of-data-science/>
Miller, Bennett, ‘Moneyball’ (Columbia Pictures, 2011)
Moro, Sérgio, Paulo Cortez, and Paulo Rita, ‘A Data-Driven Approach to Predict the Success of Bank Telemarketing’, Decision Support Systems, 62 (2014), 22–31 <https://doi.org/10.1016/j.dss.2014.03.001>
Pious, Kevin, ‘Interacting With Stakeholders as a Business Analyst: Who Are You Dealing With? | Captech Consulting’, 2013 <https://web.archive.org/web/20151015043859/https://www.captechconsulting.com/blogs/interacting-with-stakeholders-as-a-business-analyst-who-are-you-dealing-with>
Provost, Foster, and Tom Fawcett, Data Science for Business (Beijing: O’Reilly, 2013) <https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973>
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013) <https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973>
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013) <https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973>
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013) <https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973>
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013)
———, Data Science for Business (Beijing: O’Reilly, 2013)
Sharda, Ramesh, Business Intelligence: A Managerial Perspective on Analytics, 3rd Edition (Boston: Pearson, 2014)
———, Business Intelligence: A Managerial Perspective on Analytics, 3rd Edition (Boston: Pearson, 2014)
Sharda, Ramesh, Dursun Delen, and Efraim Turban, Business Intelligence: A Managerial Perspective on Analytics, 3rd Edition (Boston: Pearson, 2014)
Sharma, Aniket S., ‘Stakeholder Analysis and Management | ExpertBA’, 2013 <https://web.archive.org/web/20161028033209/http://expertbusinessanalyst.com/stakeholder-analysis-and-management/>
Sherman, Rick, Business Intelligence Guidebook: From Data Integration to Analytics (Amsterdam: Morgan Kaufmann, 2014)
———, Business Intelligence Guidebook: From Data Integration to Analytics (Amsterdam: Elsevier/Morgan Kaufmann, 2015) <https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1832704>
‘SIGKDD’ <http://kdd.org/>
‘TDWI | Advancing All Things Data | Business Intelligence, Data Warehousing, Analytics | Education & Research’ <https://tdwi.org/Home.aspx>
‘Teradata University Network’ <http://www.teradatauniversitynetwork.com/>
‘The Case for Data Ethics | Accenture Outlook’ <https://www.accenture.com/gb-en/insight-outlook-case-data-ethics>
‘Top 10 Strategic Technology Trends for 2017: Artificial Intelligence and Advanced Machine Learning’ <https://www.gartner.com/document/code/319573?ref=grbody&refval=3645332>
‘UCI Machine Learning Repository: Data Sets’ <https://archive.ics.uci.edu/ml/datasets.php>
‘UK Government Statistics’ <https://www.gov.uk/government/statistics>
‘U.S. Data and Statistics | USA.Gov’ <https://www.usa.gov/statistics>
‘Watson and the Jeopardy! Challenge’, 2014 <https://www.youtube.com/watch?v=_Xcmh1LQB9I>
‘Webinars and Videos On Demand’ <https://www.rstudio.com/resources/webinars/?mkt_tok=eyJpIjoiWVdNNFltTXlaREUxWlRVMyIsInQiOiJlZ0NHNkIzc0tPTTNldzFmaHNFaU5YOGJFcEVSZU81NWpxYThOb0ZFZGVIWjFaSTc1cFFtZzQ0cWxNbU9MMW1seFFKSGZ2aXFjZ1pSRGs5UFRnYkt2Wko1a1lcLzNcL1hFblZxRkdOWXpGTVF3PSJ9>
‘Welcome! | Score a Hit!’ <https://web.archive.org/web/20160704080559/http://www.scoreahit.com/>
Wick, Angela, ‘Six Effective Elicitation Questions to Ask Your Stakeholders | BA Times’, 2012 <http://www.batimes.com/articles/six-effective-elicitation-questions-to-ask-your-stakeholders.html>
Zhang, Chengqi, and Shichao Zhang, Association Rule Mining (Springer Berlin Heidelberg)
Zumel, Nina, and John Mount, Practical Data Science With R (Shelter Island, NY: Manning, 2014) <https://www.safaribooksonline.com/library/view/-/9781617291562/?ar>
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, NY: Manning, 2014) <https://www.safaribooksonline.com/library/view/-/9781617291562/?ar>
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, NY: Manning, 2014) <https://www.safaribooksonline.com/library/view/-/9781617291562/?ar>
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, New York: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, NY: Manning Publications Co, 2014)
———, Practical Data Science With R (Shelter Island, New York: Manning Publications Co, 2014)
