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Business Intelligence Trends 商業智慧趨勢 商業智慧導入與趨勢 (Business Intelligence Implementation and Trends) 1012BIT08 MIS MBA Mon 6, 7 (13:10-15:00) Q407 Min-Yuh Day 戴敏育 Assistant Professor 專任助理教授 Dept. of Information Management, Tamkang University 淡江大學 資訊管理學系 http://mail. tku.edu.tw/myday/ 2013-05-27 1
課程大綱 (Syllabus) 週次 日期 內容（Subject/Topics） 1 102/02/18 商業智慧趨勢課程介紹 (Course Orientation for Business Intelligence Trends) 2 102/02/25 管理決策支援系統與商業智慧 (Management Decision Support System and Business Intelligence) 3 102/03/04 企業績效管理 (Business Performance Management) 4 102/03/11 資料倉儲 (Data Warehousing) 5 102/03/18 商業智慧的資料探勘 (Data Mining for Business Intelligence) 6 102/03/25 商業智慧的資料探勘 (Data Mining for Business Intelligence) 7 102/04/01 教學行政觀摩日 (Off-campus study) 8 102/04/08 個案分析一 (SAS EM 分群分析)： Banking Segmentation (Cluster Analysis – KMeans using SAS EM) 9 102/04/15 個案分析二 (SAS EM 關連分析)： Web Site Usage Associations ( Association Analysis using SAS EM) 2
課程大綱 (Syllabus) 週次 日期 內容（Subject/Topics） 10 102/04/22 期中報告 (Midterm Presentation) 11 102/04/29 個案分析三 (SAS EM 決策樹、模型評估)： Enrollment Management Case Study (Decision Tree, Model Evaluation using SAS EM) 12 102/05/06 個案分析四 (SAS EM 迴歸分析、類神經網路)： Credit Risk Case Study (Regression Analysis, Artificial Neural Network using SAS EM) 13 102/05/13 文字探勘與網路探勘 (Text and Web Mining) 14 102/05/20 意見探勘與情感分析 (Opinion Mining and Sentiment Analysis) 15 102/05/27 商業智慧導入與趨勢 (Business Intelligence Implementation and Trends) 16 102/06/03 商業智慧導入與趨勢 (Business Intelligence Implementation and Trends) 17 102/06/10 期末報告1 (Term Project Presentation 1) 18 102/06/17 期末報告2 (Term Project Presentation 2) 3
Outline • Business Intelligence Implementation • Business Intelligence Trends • Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses 4
Business Intelligence Implementation CSFs Framework for Implementation of BI Systems Yeoh, W., & Koronios, A. (2010). Critical success factors for business intelligence systems. Journal of computer information systems, 50(3), 23. 6
Critical Success Factors of Business Intelligence Implementation • Organizational dimension – Committed management support and sponsorship – Clear vision and well-established business case • Process dimension – Business-centric championship and balanced team composition – Business-driven and iterative development approach – User-oriented change management. • Technological dimension – Business-driven, scalable and flexible technical framework – Sustainable data quality and integrity Yeoh, W., & Koronios, A. (2010). Critical success factors for business intelligence systems. Journal of computer information systems, 50(3), 23. 7
Business Intelligence Trends 1. Agile Information Management (IM) 2. Cloud Business Intelligence (BI) 3. Mobile Business Intelligence (BI) 4. Analytics 5. Big Data Source: http://www.businessspectator.com.au/article/2013/1/22/technology/five-business-intelligence-trends-2013 9
Business Intelligence Trends: Computing and Service • Cloud Computing and Service • Mobile Computing and Service • Social Computing and Service 10
Business Intelligence and Analytics • Business Intelligence 2.0 (BI 2.0) – Web Intelligence – Web Analytics – Web 2.0 – Social Networking and Microblogging sites • Data Trends – Big Data • Platform Technology Trends – Cloud computing platform Source: Lim, E. P., Chen, H., & Chen, G. (2013). Business Intelligence and Analytics: Research Directions. ACM Transactions on Management Information Systems (TMIS), 3(4), 17 11
Business Intelligence and Analytics: Research Directions 1. Big Data Analytics – Data analytics using Hadoop / MapReduce framework 2. Text Analytics – From Information Extraction to Question Answering – From Sentiment Analysis to Opinion Mining 3. Network Analysis – Link mining – Community Detection – Social Recommendation Source: Lim, E. P., Chen, H., & Chen, G. (2013). Business Intelligence and Analytics: Research Directions. ACM Transactions on Management Information Systems (TMIS), 3(4), 17 12
Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses 13
Big Data: The Management Revolution Source: McAfee, A., & Brynjolfsson, E. (2012). Big data: the management revolution.Harvard business review. 14
Source: McAfee, A., & Brynjolfsson, E. (2012). Big data: the management revolution.Harvard business review. 15
Source: http://www.amazon.com/Enterprise-Analytics-Performance-Operations-Management/dp/0133039439 16
Business Intelligence and Enterprise Analytics • Predictive analytics • Data mining • Business analytics • Web analytics • Big-data analytics Source: Thomas H. Davenport, "Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data", FT Press, 2012 17
Three Types of Business Analytics • Prescriptive Analytics • Predictive Analytics • Descriptive Analytics Source: Thomas H. Davenport, "Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data", FT Press, 2012 18
Three Types of Business Analytics Optimization “What’s the best that can happen?” Prescriptive Analytics Randomized Testing “What if we try this?” Predictive Modeling / “What will happen next?” Forecasting Predictive Analytics Statistical Modeling “Why is this happening?” Alerts “What actions are needed?” Query / Drill Down “What exactly is the problem?” Descriptive Analytics Ad hoc Reports / “How many, how often, where?” Scorecards Standard Report “What happened?” Source: Thomas H. Davenport, "Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data", FT Press, 2012 19
Big-Data Analysis • Too Big, too Unstructured, too many different source to be manageable through traditional databases 20
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