See It in SPSS: Data Mining with Clementine
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See It in SPSS: Data Mining with Clementine Prety Widjaja Systems Engineer SPSS Inc.
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Transcript of See It in SPSS: Data Mining with Clementine
See It in SPSS: Data Mining with Clementine
Prety WidjajaSystems EngineerSPSS Inc.
Agenda
Data Mining Myths
Data Mining Definition
Data Mining Methodology
Clementine Demonstration
Customer Success Stories
Q&A
Data Mining Myths
Is all about algorithms
Requires massive amount of data
Requires a data warehouse
What is Data Mining?
“The process of discovering meaningful new relationships, patterns and trends by sifting through data using pattern
recognition technologies as well as statistical and mathematical techniques.”
The Gartner Group
What is Data Mining?
Discovering meaningful patterns in your data
What is Data Mining?
As the data grows…
the relationships become more complicated.
Data Mining: Defined
Data driven approach to problem solving
Focused on Organizational Objectives
Leverages organizational data
Uncovers patterns using predictive analytics
Uses results to help improve decision making and organizational performance
EnterpriseDataSources
Marketing
Attitudinal
Interaction
Web
Call-center
Operational
Customer Contact Channels
Website
Phone
Branch
ATM
Agent
Mobile…Behavioral data- Orders- Transactions- Payment history- Renewal history
Descriptive data- Attributes- Characteristics- Self-declared info- (Geo)demographics
Attitudinal data- Opinions- Preferences- Needs- Desires
Interaction data- Offers- Results- Context- Click streams- Notes
Data at the Heart of thePredictive Enterprise
Common Applications in Business Enterprise
Customer Analytics
Process Improvement
Resource Management
Fraud and Risk Detection
Common Applications in Public Sector
Tax and Revenue: Reduce the ‘tax gap’ Improve audit selection
Law Enforcement: Effective force deployment Reduce crimes
Fraud, Waste and Abuse: Detect errors and improper payments
Resource Management
Education: Administration and Institutional Research Donor and alumni Development Educators/Teaching
Where do you start?
CRISP-DM Methodology
Cross Industry Standard Process for Data Mining
Focused on business issues Consortium of partners:
SPSS NCR/Teradata Daimler-Benz OHRA
Application neutral Industry neutral
SPSS Data Mining Workbench: Clementine
Unparalleled productivity Intuitive visual interface Breadth of techniques for modeling Multi-modeling execution
Leverages your IT database investment Access various data formats Join multiple data files
Full integration with SPSS Base
Scalable
Deployment Various exporting formats Scoring new data
Demonstration
Business Challenge: identify profiles of employees that are at high risk of leaving the organization (churn).
Results in Simple Terms:
Rule 4 for Employee departure (20 employees in this group, 90% confidence)
If Found Work Enjoyable = Yes And Received Benefits = No And Mentioned Compensation = Yes And Mentioned Perks = No And Work Facility = Facility A
Then Employee Departed
Summary
Industry standard process
Open system
Easy to use graphic interface
Flexibility
Productivity
More successful applications of predictive analytics
Some examples…
Credit Suisse’s Marketing Campaign
Increase profitability
Retain customers
Reduce cost by 50% over a 2 year period
Increase profitability
Retain customers
Reduce cost by 50% over a 2 year period
Education Institution
Increased tuition revenue
Reduced Marketing costs
Improved curriculum offerings
Improved student retention
Results
Tax and Revenue
Results
Reduced State Tax Gap
Recovered $400 million in unpaid taxes over a five-year period
Data Mining Tools Leader
Leader: Gartner Magic Quadrant 1/2006
Leader MetaSpectrum Analysis 10/2004
Most popular data mining technology 5 years running at www.kdnuggets.com
Recent Awards
SPSS Inc. was included in the listing of the annual DM Review 100, which constitutes the top 100 companies in the business intelligence space as determined by DM Review readers.
KDnuggets News, a data mining and knowledge discovery newsletter, polled more than 600 of its readers, to find out which data mining tool they regularly used. The #1 response was SPSS Inc.'s Clementine data mining workbench, for the 4th year in a row.
SPSS Inc. was ranked first in the Intelligent Enterprise “2004 Companies to Watch.” These awards highlight companies that provide the strongest vision, market leadership and technology innovation.
Question and Answer
For More Information
In case you missed it: recorded version and slides available at www.spss.com/events
Visit www.spss.com/clementine to learn more about the platform
Call us at 1-800-543-2185 or [email protected]
Please fill out the post event survey
