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Data Mining

Data Mining. Introduction BIM. Objectives. Nature of Data Mining Data Mining Tools Ethics Online Survey Techniques Interpret Data. Overview. Data Mining (data or knowledge discovery)

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Data Mining

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  1. Data Mining Introduction BIM

  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 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

  9. Analysis • Analyzes relationships and patterns using queries • Classes • Clusters • Associations • Sequential patterns

  10. Issues & Ethics • Data Integrity • Cost • Individual Privacy • Fair Use Guidelines • Federal Trade Commission • Examples • Survey Monkey Privacy Policy • Survey Monkey Terms of Use

  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

  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 2/18/2011 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

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