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ACCTG 6910 Building Enterprise & Business Intelligence Systems (e.bis)

ACCTG 6910 Building Enterprise & Business Intelligence Systems (e.bis). From Information Management to Knowledge Management. Olivia R. Liu Sheng, Ph.D. Emma Eccles Jones Presidential Chair of Business. Business Intelligence. We are drowning in data , but starving for knowledge

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ACCTG 6910 Building Enterprise & Business Intelligence Systems (e.bis)

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  1. ACCTG 6910Building Enterprise & Business Intelligence Systems(e.bis) From Information Management to Knowledge Management Olivia R. Liu Sheng, Ph.D.Emma Eccles Jones Presidential Chair of Business

  2. Business Intelligence • We are drowning in data, but starving for knowledge • Business intelligence (BI) is knowledge extracted from data to support better business decision making.

  3. Data, Information, Knowledge • Data is a set of discrete, objective facts about events. E.g., Tony’s academic record: • Fall 2001: 3 A’s • Spring 2002: 3 A’s, 2 B’s and 1 C • Fall 2002: 3 A’s and 4 C’s • Information is meaningful data. E.g., how is Tony doing academically? • Knowledge is hidden patterns extracted from data. E.g., how to improve Tony’s or any one’s academic performance?

  4. Data, Information, Knowledge Online bookstore Example: July’s revenue is $2 million Information July’s sale is bad. Knowledge Suggest marketing strategy to boost sales Data

  5. Information Age : What is lacking here • The Reason: Operational vs. Strategic Use of Data • Operational Use of Data: • The goal is to automate the business processes. • Major concern is speed and efficiency intransaction processing • Strategic Use of Data: • The goal is to collect, acquire, and use the knowledge extracted from data • Major concern is flexibility and responsiveness indecision support

  6. Building BI Systems • Data Warehouse: To organize, store and publish integrated decision support data • Data mining: Techniques to extract hidden patterns from data.

  7. What’s the Excitement About Data Warehouse Technology? The top three most important technologies ranked by IT managers in 2000-2001 (Recent surveys by The Data Warehousing Institute and Deloitte Research, http::/www.sas.com/news/feature/21aug01/ dwdemand.html/) • Internet • Data warehousing • E-commernce

  8. Brain-machine interfaces Flexible transistors Data mining Digital rights management Biometrics Natural language processing Microphotonics Untangling code Robot design Microfluidics What’s the Excitement about Data Mining Technology? 10 emerging technologies that will change the world (MIT’s Magazine of Innovation, 2001 Annual Innovation Issue)

  9. Target Marketing Credit Scoring Sales Forecasting Promotion Analysis Distribution Channel Analysis Customer Profiling Customer Profitability Analysis Cross Sell/Up Sell Help Desk Problem Resolution Customer Service Automation Network Forecasting Tariff Modeling E-government Fraud detection Security Management Product/Product Line Profitability Merchandise Planning Resource Management Operations Management Capacity Management Store/Branch Performance Analysis Store/Branch Site Selection Diagnosis decision support Gene and protein analysis Homeland Security Many Applications

  10. Course Objectives • Basic concepts and techniques • GUI tools-oriented implementation • Real world oriented learning • A few managerial issues • Promoting data warehouse and data mining career interests and opportunities

  11. A general ebusiness technology course A technical Java and web programming course A purely managerial course A course specifically on business intelligence technologies for ebusiness A hands-on course with DB and data mining implementations using tools A course emphasizing on business and data analysis and good project management practices The Course IS IS Not

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