Educating “Business Analytics Practitioner”

1. Educating “Business Analytics Practitioner” University of Technology Sydney Simeon J. Simoff

2. Outline • The “data miner” profession • Existing degrees • UTS approach • SAS contribution and collaboration <c> 2005, Simeon J. Simoff

3. The “Data miner” profession Phillipa Yelland, “Sifting through the stats”,Australian Personal Computer magazine, March 2002 • “Data mining is one of the least-understood ‘new’ areas in IT careers.” • “… business intelligence tools and services (the polite face commercial data mining likes to wear) will be a $24 billion market by 2005. <c> 2005, Simeon J. Simoff

4. Data miners Data miners are the SAS of the IT industry, and it's not a job for beginners.Demand is strong for people who have the technical skills combined with business knowledge. "To produce useable results, data miners must draw on advanced analytical approaches such as predictive modeling, association discovery and sequence discovery.“ Peter NorrisBusiness ManagerComputer Associates <c> 2005, Simeon J. Simoff

5. Data Miners • “The required blend of skills makes good data miners a rare breed.” Ronnie ChanseniorIT specialistIBM's DB2 team • "To this shopping basket of skills, add an investigative mind and enthusiasm. Above all, a good data miner must be persistent." Darren AdamsManaging DirectorConcord Communications • While the “data miner” has not quite cut it as a professional title, the mining industry has not logged any complaints to date! [8 September 2004] Tatiana Andronache, Sympatico Inc., Toronto, Canada <c> 2005, Simeon J. Simoff

6. Data Mining and Business Intelligence Increasing potential to support business decisions Data miner End User MakingInformed Decisions Business Analyst Information Presentation Visualization Techniques Data Mining & Business metrics Data Analyst Information Discovery Data Exploration Statistical Analysis, Querying and Reporting Data Warehouses / Data Marts OLAP, MDA DBA Data Sources Paper, Files, Information Providers, Database Systems, OLTP <c> 2005, Simeon J. Simoff

7. Degrees in Data Mining (not complete, but …) • Coursework Master degrees in Data Mining • Central Connecticut State University (USA)[Master of Science in Data Mining] • University of Central Florida (USA) [Dept of Stats] [with SAS][Master of Science in Data Mining] • University of Denver [College of Business][Master of Science in Data Mining] • Wessex Institute of Technology (UK) &the University of Radioelectronics, Ukraine[International Master Degree in Information Systems, Data Mining & Knowledge Discovery] • Part of the PhD research degrees in many universities <c> 2005, Simeon J. Simoff

8. UTS Coursework degrees in data mining • Master of Science in Professional Computing[Specialisation in Data Mining] [12 subjects]http://it.uts.edu.au/course/postgrad/PROFCOMP.pdf • Master of Science in Advanced Computing [Extended][Specialisation in Data Mining] [16 subjects]http://it.uts.edu.au/course/postgrad/ADVCOMP.pdf • More on the degrees http://it.uts.edu.au/course/postgrad/local/ <c> 2005, Simeon J. Simoff

9. MSc in Professional Computing (DM) • Oriented to Industry Practitioners • Course materials: • Theoretical aspects in the context of practice • Practical labs in the context of real world tools and problems [working with GB data sets] • Assignments – real world problems [ideally should come from student workplace] <c> 2005, Simeon J. Simoff

10. Data Mining: Confluence of Disciplines Database Technology Statistics Data Mining Artificial Intelligence Visualisation • HCI • Software Engineering • High Performance Computing InformationScience Other Disciplines <c> 2005, Simeon J. Simoff

11. 32130 Principles and Practice of Data Mining 32131 Data Mining and Visualisation in e-Business 32146 Data and Information Visualisation Choice from 6Computing/IT subjects 32513 Advanced Machine Learning + Choice from 8 Business subjects + Choice from 4e-Business Technology subjects 32150 Multimedia Data Mining Choice from 6 Statistical subjects Choice from 4HCI subjects 32008 Data Mining in Bioinformatics Choice from 6 Computer Graphics and Digital Media subjects Choice from 4Software engineering subjects <c> 2005, Simeon J. Simoff

12. SAS Enterprise Miner, Text Miner, etc. • 32130 Principles and Practice of Data Mining • exposes students to a broad range of tools • SAS EM – illustrates the notion of “integrated data mining environment” and “data mining as a process” • Major assignment – uses SAS EM • 32130 Data Mining and Visualisation in e-Business • SAS EM + Text Miner: main tools (plus a number of Web mining tools (usage and content) and Web mining bots • Some students go straight in the businesses, others go on further strengthening of their practical skills in SAS programming. <c> 2005, Simeon J. Simoff

13. SAS support to these degrees • SAS EM licensing • SAS prizes for best student projectin 32130 Principles and Practice of Data Miningin 31040 Data Mining and Knowledge Discovery • SAS guest lecturers (Doug Campbell, Peter O’Hanlon) • Next step: “Deeper” engagement of students in projects with SAS. <c> 2005, Simeon J. Simoff

14. Interested [in any role] Simeon J. Simoff Faculty of Information TechnologyUniversity of Technology Sydney Tel: 9514 1103Fax: 9514 1807email: simeon@it.uts.edu.au <c> 2005, Simeon J. Simoff