1. Introduction
BIM
Data Mining

2. Objectives Nature of Data Mining Data Mining Tools Ethics
Online Survey Techniques
Interpret Data

3. Overview Data Mining (data or knowledge discovery)
Definition - the process of analyzing data from different perspectives and summarizing it into useful information
Uses - increase revenue, cut costs, or both.
Examples of data mining tools
Database software programs - Access or Oracle
Online programs - Survey Monkey or GoogleDocs

4. Example Kroger card Point-of-Sale Records Targeted Promotions
Develop Products
Increase Revenue
Promotions
Coupons

5. Discuss With the person at your table
Think of an example of how a business you are familiar with can use data mining to increase sales or reduce costs
Record your response and be prepared to tell the rest of the class about it

6. Vocabulary
Data - any facts, numbers, or text that can be processed by a computer
Operational or Transactional Data – Sales, Cost, Inventory, Payroll, Accounting
Nonoperational Data – Industry Sales, Forecast Data, Macro Economic Data
Meta Data - data about the data itself
Demographic – a vital or social statistic of a human population (see example: City of Allen Demographics – population, age, male/female, education)

7. Relationships Internal External Analyze Detailed Transactional Data
Data Mining Video
Internal
Price
Product Positioning
Staff skills
External
Economic Indicators
Competition
Customer Demographics
Analyze
Sales
Customer Satisfaction
Corporate Profits
Detailed Transactional Data

8. Five Major Elements Extract Store and manage Share information Analyze
Present
Extract, transform, and load transaction data onto the data warehouse system.
Store and manage the data in a multidimensional database system.
Provide data access to business analysts and information technology professionals.
Analyze the data by application software.
Present the data in a useful format, such as a graph or table.

9. Analysis Analyzes relationships and patterns using queries Classes
Clusters
Associations
Sequential patterns
Analyzes relationships and patterns in stored transaction data based on open-ended user queries.
Classes: Stored data is used to locate data in predetermined groups. For example, a restaurant chain could mine customer purchase data to determine when customers visit and what they typically order. This information could be used to increase traffic by having daily specials.
Clusters: Data items are grouped according to logical relationships or consumer preferences. For example, data can be mined to identify market segments or consumer affinities.
Associations: Data can be mined to identify associations. The beer-diaper scenario is an example of associative mining.
Sequential patterns: Data is mined to anticipate behavior patterns and trends. For example, an outdoor equipment retailer could predict the likelihood of a backpack being purchased based on a consumer's purchase of sleeping bags and hiking shoes.

10. Issues & Ethics Data Integrity Cost Individual Privacy
Fair Use Guidelines
Federal Trade Commission
Examples
Survey Monkey Privacy Policy
Survey Monkey Terms of Use
Data Integrity - Challenge is integrating conflicting or redundant data from different sources.
Cost - Larger, faster systems needed to handle large volume of data are more expensive.
Individual Privacy - Data mining makes it possible to analyze routine business transactions and glean a significant amount of information about individuals buying habits and preferences.

11. Discuss With the person at your table
How could data mining affect your privacy?
Use the Internet to research your legal right to privacy
Write a paragraph summarizing your discussion and findings
Web mining does, however, pose a threat to some important ethical values like privacy and individuality. Web mining makes it difficult for an individual to autonomously control the unveiling and dissemination of data about his/her private life. To study these threats, we distinguish between `content and structure mining'' and `usage mining.'' Web content and structure mining is a cause for concern when data published on the web in a certain context is mined and combined with other data for use in a totally different context. Web usage mining raises privacy concerns when web users are traced, and their actions are analyzed without their knowledge ( )
Customer rights to privacy (

12. Data Mining for School Store
Setup an account on Survey Monkey
Create Online Survey
Name of Store
Items to Sell
Hours of Operation
Dates of Operation
Customer Demographics
Name
Grade
Gender

13. Assignment Table Partners Create a survey for an event
10 questions - at least 3 demographic
Get at least 20 people to take your survey
Take a minimum of 5 surveys listing their names.
Analyze the data
Develop a presentation

14. Presentation Requirements
The objective of your survey
Your 8-10 survey questions
Summary of the data collected
A minimum of one graph of the data collected
A conclusion of what actions would be taken based on your survey results
A list of what surveys your group took

15. Sources
Overview – accessed on 2/18/
Ethical Issues – accessed on 2/18/2011
Customer privacy – accessed on 2/18/2011