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Computing and University Education in Analytics. ACM Education Council San Francisco, CA November 2, 2013 Heikki Topi, Bentley University. McKinsey Global Institute Report. - PowerPoint PPT Presentation
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© Heikki Topi
Computing and University Education in Analytics
ACM Education CouncilSan Francisco, CA
November 2, 2013
Heikki Topi, Bentley University
McKinsey Global Institute ReportManyika et al. (2011). Big data: The next frontier for
innovation, competition, and productivity. McKinsey Global Institute.
Highly influential in bringing big data, big data analytics and analytics in general to the mainstream conversation
Some highlights from the intro to this report: “40% projected growth in global data gathered vs. 5%
growth in global IT spending” “140,000 – 190,000 more deep analytical talent positions
and 1.5 million more data-savvy managers needed to take full advantage of big data in the U.S.”
McKinsey Global Institute Report
High level of hype but also useful recognition of an area
(yet another) that fundamentally depends on
computing
Analytics: Simple, but Useful Categorization (Watson, 2013)Descriptive analytics
Reporting, OLAP, dashboard, scorecards, data visualization
Predictive analyticsRegression analysis, factor analysis, neural networks
Prescriptive analyticsFocuses on system performance optimizationForecasting and mathematical programming
Watson, H. (2013) The Business Case for Analytics. BizEd Magazine, July.
Davenport, Barth, & Bean (SMR 2012): Data ScientistData scientists “understand analytics, but they
also are well versed in IT, often having advanced degrees in computer science, computational physics, or biology- or network-oriented social sciences.”
“Their upgraded data management skills set – including programming, mathematical and statistical skills, as well as business acumen and the ability to communicate effectively with decision-makers – goes well beyond what was necessary for data analysts in the past”
Advanced Analytics: None of the Disciplinary Requirements Trivial Computer science
Algorithms and data structures Machine learning Parallel and distributed computing HCI – data visualization Core technologies (e.g., Hadoop, Cassandra, HDFS, Hbase, Hive,etc.)
Statistics Association rule learning Cluster analysis, classification, regression, factor analysis Neural networks Network analysis
Information science Advanced natural language processing methods Sentiment analysis
Advanced Analytics: None of the Disciplinary Requirements TrivialInformation Systems
Organizational data and database managementData qualityRequirements analysis – applying computing to a
domain Impact analysis and forecasting
Information Technology Implementing and managing increasingly complex
infrastructure requirements
© Heikki Topi
Source: http://www.informationweek.com/big-data/slideshows/big-data-analytics/big-data-analytics-masters-degrees-20/240145673
Sample Degrees from the IW listBentley University, McCallum Graduate School of Business:
Master of Science in Business AnalyticsCMU, Heinz College of Public Policy and Information Systems:
Master of Information Systems Management with a concentration in Business Intelligence and Data Analytics
Columbia University, The Fu Foundation School of Engineering and Applied Science: Master of Science in Computer Science, concentration in Machine Learning
DePaul University, College of Computing and Digital Media: Master of Science in Predictive Analytics
Drexel University, LeBow College of Business: Master of Science in Business Analytics
Sample DegreesHarvard University, School of Engineering and Applied
Sciences: Master of Science in Computational Science and Engineering
Louisiana State University, Ourso College of Business: Master of Science in Analytics
NYU, Stern School of Business: MBA, specialization in Business Analytics
Stanford University, School of Engineering (CS): Master of Science in Computer Science, Specialization in Information Management and Analytics
UC Berkeley, College of Engineering (EE and CS): Master of Engineering, concentration in Data Science and Systems
Sample DegreesUniversity of Illinois at Urbana-Champaign,
Graduate College, Department of Statistics: Master of Science in Statistics, Analytics concentration
University of Ottawa, Telfer School of Management, School of IT and Engineering and Faculty of Law: Master in Electronic Business Technologies
Advanced Analytics: Multiple Disciplinary StakeholdersMathematicsStatisticsComputer ScienceInformation SystemsEconometricsDomain expertise (e.g., various medical fields,
marketing, manufacturing control, extraction of natural resources, finance, utilities, scientific disciplines) Intensive competition for control over degree programs
Questions for Computing EducationAre we capable of collaborating with all
necessary disciplines?How do we manage a number of competing
relationships and offer truly integrated degrees?
How do we determine which discipline(s) take the leadership role in integrated programs?
Computing for the 1.5 million “data-savvy managers”? (MGI)
More Questions for Computing EducationHow do we manage the competition for
talented students?What is our role in analytics curriculum
development?Yet another reason to push for more and more
advanced computing for everybody?