Title: See it in SPSS
1See it in SPSS
- A series of in-person or online opportunities for
SPSS customers to find out about new and existing
SPSS products. - Product demonstrations
- Product previews
- QA with SPSS experts
Upcoming Events Online Clementine for
Commercial Sector Feb. 24 In-Person Chicago
Feb. 24 Atlanta April 22
For more information or to register, go to
www.spss.com/seeit
2See it in SPSS Clementine for Higher Education
- Prety Widjaja
- Systems Engineer
- February 10, 2004
3Todays Agenda
- Challenges in higher education
- Data mining defined
- Data mining in higher education
- Case studies
- Clementine demonstration
4Challenges in Higher Education
- Institutional effectiveness
- Student learning outcome assessment
- Enrollment management
- Achieving optimum attraction, retention and
persistence goals - Marketing
- Increasing competition for students
- Alumni
5Institutional effectiveness
Getting to know your students
- Which students make greatest use of institutional
services? - What courses provide high full-time equivalent
students (FTES) and allow better use of space? - What are the patterns in course taking?
- What courses tend to be taken as a group?
6Enrollment management
Helping your students succeed
- Who are our best students?
- Where do our students come from?
- Who is most likely to return for another
semester? - Who is most likely to fail or drop out?
7Marketing
Making the best use of tight budgets
- Who is most likely to respond to our new
campaign? - Which type of marketing/recruiting works best?
- Where should we focus our advertising and
recruiting?
8Alumni
Continuing the relationship
- What are the different types/groups of alumni?
- Who is likely to pledge, for how much, and when?
- Where and on whom should we focus our fundraising
drives?
9What is Data Mining?
- The process of discovering meaningful new
correlations, patterns, and trends by sifting
through large amounts of data stored in
repositories and by using pattern recognition
technologies as well as statistical and
mathematical techniques. - The Gartner Group
10Data mining
- Is
- A user-centric, interactive process which
leverages analysis technologies and computing
power - Computers and algorithms dont mine data people
do! - Is not
- Blind application of analysis/modeling algorithms
- Brute-force crunching of bulk data
-
11Data Mining Methodology
CRISP-DM industry standard data mining
methodology
12Data Mining with Clementine
- Industry-leading workbench for data mining
- Comprehensive range of tools for all stages of
the data mining process - Pioneered visual approach for maximum
productivity - Multiple modeling techniques to predict future
events
13Case Studies
14Case Studies
- Babson College
- Challengeprovide innovative curriculum for their
graduate students to gain a competitive advantage
in the business world - Solutionintegrating SPSS Incs Clementine into
their MBA curriculum - Result
- Provided students ability to understand and
synthesize data - Increased software investment by identifying
additional applications
15Case Studies
- Cabrillo College
- Challenge Identify student enrollment patterns
and tendencies - Approach
- Use a combination of both segmentation and
clustering techniques to establish typologies and
to understand grouping dynamics as well as
predictive modeling. - Predict students probability of completing a
class, transferring out, or leaving the school
altogether - Results
- Reduced marketing costs and improved curriculum
offerings - Increased revenue through student retention
16Case Studies
Data Mining and Knowledge Management, Jing
Luan, Ph.d., Terrence Willett, M.S.
- Challenge Prediction of students who will be
placed on academic probation. - Approach produce early warning model by using
rule induction C5.0 algorithm. - Result Identify high risk students and provide
academic assistance where necessary
17Clementine Demonstration
If you are not automatically taken to the "Shared
Application" screen during the demonstration,
please click on the "Shared Application" button
at the bottom of your screen.
18Benefit
- Unparalleled productivity
- Workflow provides complete support of the
complete CRISP-DM methodology - Breadth of techniques for modeling and processing
- Openness
- Leverages investment in existing systems
- Scalability
- Scales the entire interactive data mining process
- Deployment
- Fast and cost-effective delivery of data mining
solutions
19Special Offer!
- Purchase Clementine by March 29th and receive 20
off the Introduction to Clementine training
class!
20More information
http//www.spss.com/clementine
21Question and answer
Sales sales_at_spss.com Technical
supporthttps//www.spss.com/tech/techtalk.htm(3
12) 651-3410 See it in SPSS eventswww.spss.com
/seeit