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商業智慧實務 Practices of Business Intelligence 1 1032BI01 MI4 Wed, 9,10 (16:10-18:00) (B130) 商業智慧導論 (Introduction to Business Intelligence) Min-Yuh Day 戴敏育

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  • Practices of Business Intelligence*1032BI01MI4Wed, 9,10 (16:10-18:00) (B130) (Introduction to Business Intelligence)Min-Yuh DayAssistant Professor Dept. of Information Management, Tamkang University

    http://mail. tku.edu.tw/myday/2015-02-25Tamkang University

  • 1032Spring 2015 (2015.02 - 2015.06) (Practices of Business Intelligence) (Min-Yuh Day)P (TLMXB4P) 2 (2 Credits, Elective) 9,10 (Wed 16:10-18:00)B130*

  • (Business Intelligence) *

  • Course IntroductionThis course introduces the fundamental concepts and technology practices of business intelligence. Topics include Introduction to Business Intelligence, Management Decision Support System and Business Intelligence, Business Performance Management, Data Warehousing, Data Mining for Business Intelligence, Data Science and Big Data Analytics, Text and Web Mining, Opinion Mining and Sentiment Analysis, Social Network Analysis.*

  • *

  • ObjectiveUnderstand and apply the fundamental concepts and technology practices of business intelligence.*

  • (Week) (Date) (Subject/Topics)1 2015/02/25 (Introduction to Business Intelligence)2 2015/03/04 (Management Decision Support System and Business Intelligence)3 2015/03/11 (Business Performance Management)4 2015/03/18 (Data Warehousing)5 2015/03/25 (Data Mining for Business Intelligence)6 2015/04/01 (Off-campus study)7 2015/04/08 (Data Mining for Business Intelligence)8 2015/04/15 (Data Science and Big Data Analytics) (Syllabus)*

  • Subject/Topics9 2015/04/22 (Midterm Project Presentation)10 2015/04/29 (Midterm Exam)11 2015/05/06 (Text and Web Mining)12 2015/05/13 (Opinion Mining and Sentiment Analysis)13 2015/05/20 (Social Network Analysis)14 2015/05/27 (Final Project Presentation)15 2015/06/03 (Final Exam) (Syllabus)*

  • (Textbook) (Slides) (References)Decision Support and Business Intelligence Systems, Ninth Edition, Efraim Turban, Ramesh Sharda, Dursun Delen, 2011, PearsonEfraim Turban 2011*

  • 330 30 40

    *

  • Team Term ProjectTerm Project TopicsData mining Web miningBusiness IntelligenceBig Data Analytics3-4 2015/03/04 () *

  • Business PressuresResponsesSupport ModelSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • Data WarehouseData Mining and Business Intelligence Increasing potentialto supportbusiness decisionsEnd UserBusiness Analyst DataAnalystDBADecision MakingData PresentationVisualization TechniquesData MiningInformation DiscoveryData ExplorationStatistical Summary, Querying, and ReportingData Preprocessing/Integration, Data WarehousesData SourcesPaper, Files, Web documents, Scientific experiments, Database Systems*Source: Han & Kamber (2006)

  • Business Intelligence (BI)BI is an umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologiesLike DSS, BI a content-free expression, so it means different things to different peopleBI's major objective is to enable easy access to data (and models) to provide business managers with the ability to conduct analysisBI helps transform data, to information (and knowledge), to decisions and finally to actionSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • A Brief History of BIThe term BI was coined by the Gartner Group in the mid-1990sHowever, the concept is much older1970s - MIS reporting - static/periodic reports1980s - Executive Information Systems (EIS)1990s - OLAP, dynamic, multidimensional, ad-hoc reporting -> coining of the term BI 2005+ Inclusion of AI and Data/Text Mining capabilities; Web-based Portals/Dashboards2010s - yet to be seenSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • The Evolution of BI CapabilitiesSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • The Architecture of BIA BI system has four major componentsa data warehouse, with its source databusiness analytics, a collection of tools for manipulating, mining, and analyzing the data in the data warehouse; business performance management (BPM) for monitoring and analyzing performancea user interface (e.g., dashboard) Source: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • A High-Level Architecture of BISource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • Components in a BI ArchitectureThe data warehouse is a large repository of well-organized historical dataBusiness analytics are the tools that allow transformation of data into information and knowledgeBusiness performance management (BPM) allows monitoring, measuring, and comparing key performance indicators User interface (e.g., dashboards) allows access and easy manipulation of other BI componentsSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • A Conceptual Framework for DWSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • A Taxonomy for Data Mining TasksSource: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • Social Network Analysis

    *Source: http://www.fmsasg.com/SocialNetworkAnalysis/

  • A Closed-Loop Process to Optimize Business Performance Process StepsStrategizePlanMonitor/analyzeAct/adjust

    Each with its own process steps Source: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • RFID for Supply Chain BIRFID in Retail SystemsSource: Turban et al. (2011), Decision Support and Business Intelligence Systems

  • Implications of Business and Enterprise Social NetworksBusiness oriented social networks can go beyond advertising and salesEmerging enterprise social networking apps: Finding and Recruiting WorkersManagement Activities and SupportTrainingKnowledge Management and Expert Locatione.g., innocentive.com; awareness.com; Caterpillar Enhancing CollaborationUsing Blogs and Wikis Within the Enterprise*Source: Turban et al. (2011), Decision Support and Business Intelligence Systems

  • Implications of Business and Enterprise Social NetworksSurvey shows that best-in-class companies use blogs and wikis for the following applications:Project collaboration and communication (63%)Process and procedure document (63%)FAQs (61%)E-learning and training (46%)Forums for new ideas (41%)Corporate-specific dynamic glossary and terminology (38%)Collaboration with customers (24%)*Source: Turban et al. (2011), Decision Support and Business Intelligence Systems

  • The Benefits of BIThe ability to provide accurate information when needed, including a real-time view of the corporate performance and its partsA survey by Thompson (2004) Faster, more accurate reporting (81%)Improved decision making (78%)Improved customer service (56%)Increased revenue (49%)Source: Turban et al. (2011), Decision Support and Business Intelligence Systems*

  • *Source: http://www.amazon.com/Big-Data-Analytics-Intelligence-Businesses/dp/111814760X

  • Business Intelligence TrendsAgile Information Management (IM)Cloud Business Intelligence (BI)Mobile Business Intelligence (BI)AnalyticsBig Data*Source: http://www.businessspectator.com.au/article/2013/1/22/technology/five-business-intelligence-trends-2013

  • Business Intelligence Trends: Computing and ServiceCloud Computing and ServiceMobile Computing and ServiceSocial Computing and Service *

  • Business Intelligence and AnalyticsBusiness Intelligence 2.0 (BI 2.0)Web IntelligenceWeb AnalyticsWeb 2.0Social Networking and Microblogging sitesData TrendsBig DataPlatform Technology TrendsCloud 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

  • Business Intelligence and Analytics: Research Directions1. Big Data AnalyticsData analytics using Hadoop / MapReduce framework2. Text AnalyticsFrom Information Extraction to Question AnsweringFrom Sentiment Analysis to Opinion Mining3. Network AnalysisLink miningCommunity DetectionSocial 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

  • *Source: Davenport, T. H., & Patil, D. J. (2012). Data Scientist.Harvard business review

  • Top 10 CIO Technology Priorities in 20151. Business Intelligence/Analytics2. Infrastructure and Data Center3. Cloud4. ERP5. Mobile6. Digitalization/Digital Marketing7. Security8. Networking, Voice & Data9. CRM10. Industry-Specific Applications*Source: Gartner, January 2015 http://www.gartner.com/newsroom/id/2981317

  • SAS *http://saschampion.com.tw/

  • *SAS http://www.accupass.com/go/saschampion

  • SummaryThis course introduces the fundamental concepts and technology practices of business intelligence. Topics include Introduction to Business Intelligence, Management Decision Support System and Business Intelligence, Business Performance Management, Data Warehousing, Data Mining for Business Intelligence, Data Science and Big Data Analytics, Text and Web Mining, Opinion Mining and Sentiment Analysis, Social Network Analysis.*

  • Contact Information (Min-Yuh Day, Ph.D.)

    02-26215656 #284602-26209737B929 25137 151Email [email protected]://

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