Data MiningBy Jason Baltazar, Phil Cademas, Jillian Latham, Rachel Peeler & Kamila Singh

What is Data Mining?Data Mining is data processing using

sophisticated data search capabilities and statistical algorithms to discover patters and correlations in large preexisting databases.

2 Broad Categories: Supervised & Unsupervised

Unsupervised Data Mining“Descriptive Modeling”

Uncover patterns and relationships among data

No predetermined parameters

Observations after analysis

Used to assist in making business decisions

Cluster Analysis “Automated Data Mining”

Used to discover the segments or groups within a customer data set

Determine classes of similar customers that naturally fit together

Demographics

Segmented Markets Marketing and Advertising

Supervised Data Mining “Predictive Modeling”

Set goals and parameters prior to data mining

Concentration: only relevant patterns

Predict outcomes

Anomaly Detection, Classification & Prediction, Regression, Analysis

Anomaly Detection Models built to specify “normal” ranges of

results

Fraud Detection Tax, insurance, credit card industries

Prevent Identity Theft

Detect breaches in computer security

PayPal 15% of all e-commerce in the U.S.

Classification & Prediction Most common data analysis tool

“Who will buy what, and how much will they buy?”

Credit analysis / Credit Scoring – Who are my “good credit risks?”

Based on spending habits, income, and/or demographics

Can be used in customer segmentation, business modeling, credit analysis, etc.

Classification & Prediction Human Resources

Turnover analysis, employee development, recruiting, training, and employee retention

Determine the “value” of employees Fill leadership/management positions from within

the organization Groom and promote based on a set of

predetermined skills, attitudes, and competencies

Regression AnalysisStatistics applies to data to make

predictions i.e. How product price and promotions

affect sales

Marketing, pricing, product positioning, sales forecasting, advertising, human relations, customer service

Objectives: market response modeling and sales forecasting

Text MiningText Mining is the process of

automatically processing text and extracting information from it

Presidential election

Text Mining ApplicationsSecurity Applications

Biomedical Applications

Online Media Applications

Academic Applications

Data Mining Advantages

Helps to reduce costs

Provides improved and more detail oriented service

Increases market effectiveness

Beneficial to all industries

Data Mining Disadvantages Privacy Issues

Access to personal information

Security Issues Insufficient security systems

Misuse of information & inaccurate information

Insurance & HealthcareTarget marketing

Helps to develop different plans and policies

Mobile CommunicationHelps develop a variety of different cell phone plans

Target marketing

Data Mining Privacy

Who has access to consumer personal information CVS Pharmacy & Marketing Companies

Data Mining Ethics: Consumers

How far is too far? Trustworthy?

Data is being collected & used

Opt out boxes What are some solutions that give consumers

control?Access to databases that have their informationThe right to change what information is available

Data Mining Ethics: Businesses

Help enhance overall customer satisfaction Profit enhancer? Violation of privacy

Sometimes partnered with marketing companies They also have access to private

information

Conclusion

ANY QUESTIONS?