1.
Provost F, Fawcett T. Data Science for Business [Internet]. Beijing: O’Reilly; 2013. Available from: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973
2.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
3.
Zumel N, Mount J. Practical Data Science With R [Internet]. Shelter Island, NY: Manning; 2014. Available from: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar
4.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
5.
Sharda R, Delen D, Turban E. Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson; 2014.
6.
Hype Cycle for Data Science, 2016 [Internet]. Available from: https://www.gartner.com/document/code/303293?ref=grbody&refval=3574217
7.
Hype Cycle for Business Intelligence and Analytics, 2016 [Internet]. Available from: https://www.gartner.com/document/code/290879?ref=grbody&refval=3574217
8.
ITScore for BI and Analytics [Internet]. Available from: https://www.gartner.com/document/code/314086?ref=grbody&refval=3574217
9.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
10.
SIGKDD [Internet]. Available from: http://kdd.org/
11.
IBM Big Data and Analytics - Case Studies - United Kingdom [Internet]. IBM Corporation; 2015. Available from: https://web.archive.org/web/20150221100253/http://www.ibm.com/big-data/uk/en/big-data-and-analytics/case-studies.html
12.
TDWI | Advancing All Things Data | Business Intelligence, Data Warehousing, Analytics | Education & Research [Internet]. Available from: https://tdwi.org/Home.aspx
13.
Decision Support Systems Resources | DSSResources [Internet]. Available from: http://dssresources.com/
14.
Teradata University Network [Internet]. Available from: http://www.teradatauniversitynetwork.com/
15.
Lehmann J, Joseph S. Biochar for Environmental Management: Science and Technology. London: Earthscan; 2009.
16.
IBM Cognos Analytics on Cloud - United Kingdom [Internet]. Available from: https://web.archive.org/web/20210604092138/https://www.ibm.com/uk-en/products/cognos-analytics
17.
Sherman R. Business Intelligence Guidebook: From Data Integration to Analytics. Amsterdam: Morgan Kaufmann; 2014.
18.
Sherman R. Business Intelligence Guidebook: From Data Integration to Analytics [Internet]. Amsterdam: Elsevier/Morgan Kaufmann; 2015. Available from: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1832704
19.
Jeet P, Vats P. Learning Quantitative Finance with R [Internet]. Packt Publishing; 2017. Available from: https://www.safaribooksonline.com/library/view/learning-quantitative-finance/9781786462411/
20.
Daróczi G, Vidovics-Dancs A, Havran D, Berlinger E, Michaletzky M, Puhle M, Csóka P, Váradi K, Tulassay Z. Introduction to R for Quantitative Finance [Internet]. Packt Publishing; 2013. Available from: https://www.safaribooksonline.com/library/view/introduction-to-r/9781783280933/
21.
Berlinger E, Illés F, Badics M, Banai Á, Daróczi G, Dömötör B, Gabler G, Havran D, Juhász P, Margitai I, Márkus B, Medvegyev P, Molnár J, Árpád Szűcs B, Tuza Á, Vadász T, Váradi K, Vidovics-Dancs Á. Mastering R for Quantitative Finance [Internet]. Packt Publishing; 2015. Available from: https://www.safaribooksonline.com/library/view/mastering-r-for/9781783552078/
22.
How to Use read.csv() to Import Data in R [Internet]. Available from: http://www.dummies.com/programming/r/how-to-use-read-csv-to-import-data-in-r/
23.
Provost F, Fawcett T. Data Science for Business [Internet]. Beijing: O’Reilly; 2013. Available from: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973
24.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
25.
Sharda R. Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson; 2014.
26.
Chapman P. CRISP-DM 1.0: Step-by-Step Data Mining Guide [Internet]. SPSS; 2000. Available from: https://the-modeling-agency.com/crisp-dm.pdf
27.
Top 10 Strategic Technology Trends for 2017: Artificial Intelligence and Advanced Machine Learning [Internet]. Available from: https://www.gartner.com/document/code/319573?ref=grbody&refval=3645332
28.
Fayyad U, Piatetsky-Shapiro G, Smyth P. The KDD Process for Extracting Useful Knowledge From Volumes of Data (Knowledge Discovery in Databases). Communications of the ACM. 1996;39(11):27–34.
29.
Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers AH. Big Data: The Next Frontier for Innovation, Competition, and Productivity | McKinsey & Company [Internet]. 2011. Available from: https://web.archive.org/web/20200606014002/https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation
30.
Brynjolfsson E. Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? SSRN Electronic Journal. 2011;
31.
Cukier KN, Mayer-Schoenberger V. Why Big Data Is on the Rise | Foreign Affairs [Internet]. 2013. Available from: https://www.foreignaffairs.com/articles/2013-04-03/rise-big-data
32.
Mason H. A Taxonomy of Data Science | Dataists [Internet]. 2010. Available from: https://web.archive.org/web/20210728133552/http://www.dataists.com/2010/09/a-taxonomy-of-data-science/
33.
Lewis M. Moneyball: The Art of Winning an Unfair Game. New York, New York: W.W. Norton & Company; 2004.
34.
Dallaway E. Ten Data-Driven Sporting Victories - Part One | Technology. The Guardian [Internet]. 2015 Mar 16; Available from: http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-one
35.
Dallaway E. Ten Data-Driven Sporting Victories - Part Two | Technology. The Guardian [Internet]. 2015 Mar 16; Available from: http://www.theguardian.com/technology/2015/mar/16/ten-data-driven-sporting-victories-part-two
36.
Hays CL. What Wal-Mart Knows About Customers’ Habits. The New York Times [Internet]. 2004 Nov 14; Available from: http://www.nytimes.com/2004/11/14/business/yourmoney/what-walmart-knows-about-customers-habits.html?_r=1
37.
Hetherington R. Preventing Customer Churn With Better Data Analytics [Internet]. 2015. Available from: https://www.digitalistmag.com/industries/banking/2015/06/23/preventing-customer-churn-with-better-data-analytics-3-02974982
38.
How to Become a Data Scientist (Part 1/3) – Towards Data Science A Medium [Internet]. Available from: 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
39.
Deloitte and Ibm, We’re Facing a Huge Uk Digital Skills Gap - Infographic | Ignite [Internet]. Available from: https://www.ignite.digital/uk-digital-skills-gap-infographic/
40.
Provost F, Fawcett T. Data Science for Business [Internet]. Beijing: O’Reilly; 2013. Available from: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973
41.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
42.
Sharda R. Business Intelligence: A Managerial Perspective on Analytics. 3rd Edition. Boston: Pearson; 2014.
43.
Zumel N, Mount J. Practical Data Science With R [Internet]. Shelter Island, NY: Manning; 2014. Available from: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar
44.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
45.
Kenny G. Five Questions to Identify Key Stakeholders. Harvard Business Review [Internet]. 2014 Mar 6; Available from: https://hbr.org/2014/03/five-questions-to-identify-key-stakeholders
46.
Sharma AS. Stakeholder Analysis and Management | ExpertBA [Internet]. 2013. Available from: https://web.archive.org/web/20161028033209/http://expertbusinessanalyst.com/stakeholder-analysis-and-management/
47.
Pious K. Interacting With Stakeholders as a Business Analyst: Who Are You Dealing With? | Captech Consulting [Internet]. 2013. Available from: https://web.archive.org/web/20151015043859/https://www.captechconsulting.com/blogs/interacting-with-stakeholders-as-a-business-analyst-who-are-you-dealing-with
48.
de Bree T. 8 Questions Every Business Analyst Should Ask | Modern Analyst [Internet]. Available from: http://www.modernanalyst.com/Resources/Articles/tabid/115/ID/179/8-Questions-Every-Business-Analyst-Should-Ask.aspx
49.
Wick A. Six Effective Elicitation Questions to Ask Your Stakeholders | BA Times [Internet]. 2012. Available from: http://www.batimes.com/articles/six-effective-elicitation-questions-to-ask-your-stakeholders.html
50.
Goodwin K. A Stakeholder Interview Checklist | Boxes and Arrows [Internet]. 2013. Available from: http://boxesandarrows.com/a-stakeholder-interview-checklist/
51.
Egger D. Business Metrics for Data-Driven Companies: 20-Item Checklist | Onyx Reporting [Internet]. Available from: https://web.archive.org/web/20210119104435/http://www.onyxreporting.com/uploads/4/0/8/5/40851971/20itemchecklist.pdf
52.
Grace-Martin K. Seven Ways to Make up Data: Common Methods to Imputing Missing Data | The Analysis Factor [Internet]. Available from: https://www.theanalysisfactor.com/seven-ways-to-make-up-data-common-methods-to-imputing-missing-data/
53.
Zumel N, Mount J. Practical Data Science With R [Internet]. Shelter Island, NY: Manning; 2014. Available from: https://www.safaribooksonline.com/library/view/-/9781617291562/?ar
54.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
55.
Provost F, Fawcett T. Data Science for Business [Internet]. Beijing: O’Reilly; 2013. Available from: https://ebookcentral.proquest.com/lib/rhul/detail.action?docID=1323973
56.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
57.
Ashenfelter O, Ashmore D, Lalonde R. Bordeaux Wine Vintage Quality and the Weather [Internet]. Available from: http://www.liquidasset.com/orley.htm
58.
Lewis M. Moneyball: The Art of Winning an Unfair Game. New York, New York: W.W. Norton & Company; 2004.
59.
Miller B. Moneyball. Columbia Pictures; 2011.
60.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
61.
Moro S, Cortez P, Rita P. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems. 2014;62:22–31.
62.
Welcome! | Score a Hit! [Internet]. Available from: https://web.archive.org/web/20160704080559/http://www.scoreahit.com/
63.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, New York: Manning Publications Co; 2014.
64.
Gerber AS, Green DP, Larimer CW. Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment. The American Political Science Review [Internet]. 2008;102(1):33–48. Available from: https://www.jstor.org/stable/27644496
65.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, NY: Manning Publications Co; 2014.
66.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
67.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
68.
Zumel N, Mount J. Practical Data Science With R. Shelter Island, New York: Manning Publications Co; 2014.
69.
Jain D, Gautam S. Implementation of Apriori Algorithm in Health Care Sector: A Survey. International Journal of Computer Science and Communication Engineering. 2(4):26–32.
70.
Hahsler M, Grun B, Hornik K, Buchta C. Introduction to Arules – A Computational Environment for Mining Association Rules and Frequent Item Sets [Internet]. Available from: https://cran.r-project.org/web/packages/arules/vignettes/arules.pdf
71.
Agrawal R, Imieliński T, Swami A. Mining Association Rules Between Sets of Items in Large Databases. ACM SIGMOD Record [Internet]. 1993;22(2):207–216. Available from: http://portal.acm.org/citation.cfm?doid=170035.170072
72.
Zhang C, Zhang S. Association Rule Mining. Springer Berlin Heidelberg;
73.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
74.
Best J. IBM Watson: The Inside Story of How the Jeopardy-Winning Supercomputer Was Born, and What It Wants to Do Next | TechRepublic [Internet]. 2013. Available from: 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/
75.
Go A, Bhayani R, Huang L. Twitter Sentiment Classification using Distant Supervision [Internet]. Available from: http://cs.stanford.edu/people/alecmgo/papers/TwitterDistantSupervision09.pdf
76.
Lee L, Pang B. Opinion Mining and Sentiment Analysis [open access]. Foundations and Trends in Information Retrieval [Internet]. 2(1–2):1–135. Available from: http://www.cs.cornell.edu/home/llee/omsa/omsa.pdf
77.
IBM’s Watson Computer Plays Jeopardy!!! | YouTube [Internet]. 2013. Available from: https://www.youtube.com/watch?v=P18EdAKuC1U
78.
Watson and the Jeopardy! Challenge [Internet]. 2014. Available from: https://www.youtube.com/watch?v=_Xcmh1LQB9I
79.
Provost F, Fawcett T. Data Science for Business. Beijing: O’Reilly; 2013.
80.
Goldfarb A, Tucker CE. Privacy Regulation and Online Advertising. Management Science. 2011;57(1):57–71.
81.
Buytendijk F, Heiser J. Confronting the Privacy and Ethical Risks of Big Data. Financial Times [Internet]. 2013 Sep 24; Available from: https://www.ft.com/content/105e30a4-2549-11e3-b349-00144feab7de
82.
The Case for Data Ethics | Accenture Outlook [Internet]. Available from: https://www.accenture.com/gb-en/insight-outlook-case-data-ethics
83.
Bertolucci J. Data Scientists Want Big Data Ethics Standards | InformationWeek [Internet]. 2014. Available from: http://www.informationweek.com/big-data/big-data-analytics/data-scientists-want-big-data-ethics-standards/d/d-id/1315798
84.
Davenport T. The Dark Side of Customer Analytics. Harvard Business Review [Internet]. 2007; Available from: http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=24635693&site=ehost-live
85.
DeAsi G. How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google) | Pointillist [Internet]. Available from: https://web.archive.org/web/20221020180045/https://www.pointillist.com/blog/customer-behavior-data/
86.
How to Use Customer Behavior Data to Drive Revenue (Like Amazon, Netflix & Google) [Internet]. Available from: https://www.pointillist.com/blog/customer-behavior-data/
87.
UCI Machine Learning Repository: Data Sets [Internet]. Available from: https://archive.ics.uci.edu/ml/datasets.php
88.
UK Government Statistics [Internet]. Available from: https://www.gov.uk/government/statistics
89.
U.S. Data and Statistics | USA.gov [Internet]. Available from: https://www.usa.gov/statistics
90.
Datasets for Data Mining and Data Science [Internet]. Available from: http://www.kdnuggets.com/datasets/index.html
91.
Webinars and Videos On Demand [Internet]. Available from: https://www.rstudio.com/resources/webinars/?mkt_tok=eyJpIjoiWVdNNFltTXlaREUxWlRVMyIsInQiOiJlZ0NHNkIzc0tPTTNldzFmaHNFaU5YOGJFcEVSZU81NWpxYThOb0ZFZGVIWjFaSTc1cFFtZzQ0cWxNbU9MMW1seFFKSGZ2aXFjZ1pSRGs5UFRnYkt2Wko1a1lcLzNcL1hFblZxRkdOWXpGTVF3PSJ9
