[1]
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.
[2]
A Stakeholder Interview Checklist | Boxes and Arrows: 2013. http://boxesandarrows.com/a-stakeholder-interview-checklist/.
[3]
A Taxonomy of Data Science | Dataists: 2010. https://web.archive.org/web/20210728133552/http://www.dataists.com/2010/09/a-taxonomy-of-data-science/.
[4]
Agrawal, R. et al. 1993. Mining Association Rules Between Sets of Items in Large Databases. ACM SIGMOD Record. 22, 2 (1993), 207–216. DOI:https://doi.org/10.1145/170035.170072.
[5]
Berlinger, E. et al. 2015. Mastering R for Quantitative Finance. Packt Publishing.
[6]
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.
[7]
Bordeaux Wine Vintage Quality and the Weather: http://www.liquidasset.com/orley.htm.
[8]
Brynjolfsson, E. 2011. Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? SSRN Electronic Journal. (2011). DOI:https://doi.org/10.2139/ssrn.1819486.
[9]
Buytendijk, F. and Heiser, J. 2013. Confronting the Privacy and Ethical Risks of Big Data. Financial Times. (Sep. 2013).
[10]
Chapman, P. 2000. CRISP-DM 1.0: Step-by-Step Data Mining Guide. SPSS.
[11]
Dallaway, E. 2015. Ten Data-Driven Sporting Victories - Part One | Technology. The Guardian. (Mar. 2015).
[12]
Dallaway, E. 2015. Ten Data-Driven Sporting Victories - Part Two | Technology. The Guardian. (Mar. 2015).
[13]
Daróczi, G. et al. 2013. Introduction to R for Quantitative Finance. Packt Publishing.
[14]
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.
[15]
Datasets for Data Mining and Data Science: http://www.kdnuggets.com/datasets/index.html.
[16]
Davenport, T. 2007. The Dark Side of Customer Analytics. Harvard Business Review. (2007).
[17]
Decision Support Systems Resources | DSSResources: http://dssresources.com/.
[18]
Deloitte and Ibm, We’re Facing a Huge Uk Digital Skills Gap - Infographic | Ignite: https://www.ignite.digital/uk-digital-skills-gap-infographic/.
[19]
Egger, D. Business Metrics for Data-Driven Companies: 20-Item Checklist | Onyx Reporting.
[20]
Fayyad, U. et al. 1996. The KDD Process for Extracting Useful Knowledge From Volumes of Data (Knowledge Discovery in Databases). Communications of the ACM. 39, 11 (1996), 27–34. DOI:https://doi.org/10.1145/240455.240464.
[21]
Gerber, A.S. et al. 2008. Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment. The American Political Science Review. 102, 1 (2008), 33–48.
[22]
Go, A. et al. Twitter Sentiment Classification using Distant Supervision.
[23]
Goldfarb, A. and Tucker, C.E. 2011. Privacy Regulation and Online Advertising. Management Science. 57, 1 (2011), 57–71. DOI:https://doi.org/10.1287/mnsc.1100.1246.
[24]
Hahsler, M. et al. Introduction to Arules – A Computational Environment for Mining Association Rules and Frequent Item Sets.
[25]
Hays, C.L. 2004. What Wal-Mart Knows About Customers’ Habits. The New York Times. (Nov. 2004).
[26]
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.
[27]
How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google): https://www.pointillist.com/blog/customer-behavior-data/.
[28]
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/.
[29]
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/.
[30]
Hype Cycle for Business Intelligence and Analytics, 2016: https://www.gartner.com/document/code/290879?ref=grbody&refval=3574217.
[31]
Hype Cycle for Data Science, 2016: https://www.gartner.com/document/code/303293?ref=grbody&refval=3574217.
[32]
IBM Big Data and Analytics - Case Studies - United Kingdom: 2015. https://web.archive.org/web/20150221100253/http://www.ibm.com/big-data/uk/en/big-data-and-analytics/case-studies.html.
[33]
IBM Cognos Analytics on Cloud - United Kingdom: https://web.archive.org/web/20210604092138/https://www.ibm.com/uk-en/products/cognos-analytics.
[34]
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/.
[35]
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.
[36]
ITScore for BI and Analytics: https://www.gartner.com/document/code/314086?ref=grbody&refval=3574217.
[37]
Jain, D. and Gautam, S. Implementation of Apriori Algorithm in Health Care Sector: A Survey. International Journal of Computer Science and Communication Engineering. 2, 4, 26–32.
[38]
Jeet, P. and Vats, P. 2017. Learning Quantitative Finance with R. Packt Publishing.
[39]
Kenny, G. 2014. Five Questions to Identify Key Stakeholders. Harvard Business Review. (Mar. 2014).
[40]
Lee, L. and Pang, B. Opinion Mining and Sentiment Analysis [open access]. Foundations and Trends in Information Retrieval. 2, 1–2, 1–135.
[41]
Lehmann, J. and Joseph, S. 2009. Biochar for Environmental Management: Science and Technology. Earthscan.
[42]
Lewis, M. 2004. Moneyball: The Art of Winning an Unfair Game. W.W. Norton & Company.
[43]
Lewis, M. 2004. Moneyball: The Art of Winning an Unfair Game. W.W. Norton & Company.
[44]
Miller, B. 2011. Moneyball. Columbia Pictures.
[45]
Moro, S. et al. 2014. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems. 62, (2014), 22–31. DOI:https://doi.org/10.1016/j.dss.2014.03.001.
[46]
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.
[47]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[48]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[49]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[50]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[51]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[52]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[53]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[54]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[55]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[56]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[57]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[58]
Provost, F. and Fawcett, T. 2013. Data Science for Business. O’Reilly.
[59]
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/.
[60]
Sharda, R. et al. 2014. Business Intelligence: A Managerial Perspective on Analytics. Pearson.
[61]
Sharda, R. 2014. Business Intelligence: A Managerial Perspective on Analytics. Pearson.
[62]
Sharda, R. 2014. Business Intelligence: A Managerial Perspective on Analytics. Pearson.
[63]
Sherman, R. 2014. Business Intelligence Guidebook: From Data Integration to Analytics. Morgan Kaufmann.
[64]
Sherman, R. 2015. Business Intelligence Guidebook: From Data Integration to Analytics. Elsevier/Morgan Kaufmann.
[65]
SIGKDD: http://kdd.org/.
[66]
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.
[67]
Stakeholder Analysis and Management | ExpertBA: 2013. https://web.archive.org/web/20161028033209/http://expertbusinessanalyst.com/stakeholder-analysis-and-management/.
[68]
TDWI | Advancing All Things Data | Business Intelligence, Data Warehousing, Analytics | Education & Research: https://tdwi.org/Home.aspx.
[69]
Teradata University Network: http://www.teradatauniversitynetwork.com/.
[70]
The Case for Data Ethics | Accenture Outlook: https://www.accenture.com/gb-en/insight-outlook-case-data-ethics.
[71]
Top 10 Strategic Technology Trends for 2017: Artificial Intelligence and Advanced Machine Learning: https://www.gartner.com/document/code/319573?ref=grbody&refval=3645332.
[72]
UCI Machine Learning Repository: Data Sets: https://archive.ics.uci.edu/ml/datasets.php.
[73]
UK Government Statistics: https://www.gov.uk/government/statistics.
[74]
U.S. Data and Statistics | USA.gov: https://www.usa.gov/statistics.
[75]
Webinars and Videos On Demand: https://www.rstudio.com/resources/webinars/?mkt_tok=eyJpIjoiWVdNNFltTXlaREUxWlRVMyIsInQiOiJlZ0NHNkIzc0tPTTNldzFmaHNFaU5YOGJFcEVSZU81NWpxYThOb0ZFZGVIWjFaSTc1cFFtZzQ0cWxNbU9MMW1seFFKSGZ2aXFjZ1pSRGs5UFRnYkt2Wko1a1lcLzNcL1hFblZxRkdOWXpGTVF3PSJ9.
[76]
Welcome! | Score a Hit! https://web.archive.org/web/20160704080559/http://www.scoreahit.com/.
[77]
Why Big Data Is on the Rise | Foreign Affairs: 2013. https://www.foreignaffairs.com/articles/2013-04-03/rise-big-data.
[78]
Zhang, C. and Zhang, S. Association Rule Mining. Springer Berlin Heidelberg.
[79]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning.
[80]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[81]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[82]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning.
[83]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[84]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning.
[85]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[86]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[87]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[88]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[89]
Zumel, N. and Mount, J. 2014. Practical Data Science With R. Manning Publications Co.
[90]
2013. IBM’s Watson Computer Plays Jeopardy!!! | YouTube.
[91]
2014. Watson and the Jeopardy! Challenge.