Introduction BIM Data Mining

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

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

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

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

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)

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

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.

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.

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.

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 (http://www.springerlink.com/content/m13883x465627814/ ) Customer rights to privacy (http://www.exforsys.com/tutorials/data-mining/data-mining-privacy-concerns.html)

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

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

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

Sources Overview – accessed on 2/18/2011 http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm Ethical Issues – accessed on 2/18/2011 http://www.springerlink.com/content/m13883x465627814/ Customer privacy – accessed on 2/18/2011 http://www.exforsys.com/tutorials/data-mining/data-mining-privacy-concerns.html