《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（习题，原书第4版）chapter 2 Descriptive Analytics I：Nature of Data, Statistical Modeling, and Visualization

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（习题，原书第4版）chapter 2 Descriptive Analytics I：Nature of Data, Statistical Modeling, and Visualization

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）08 Future Trends, Privacy and Managerial Considerations in Analytics

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）06 Prescriptive Analytics：Optimization and Simulation

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）04 Predictive Analytics I：Data Mining Process, Methods, and Algorithms

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）02 Descriptive Analytics I：Nature of Data, Statistical Modeling, and Visualization

5.1 Describe text mining and understand the need for text mining 5.2 Differentiate among text analytics, text mining, and data mining 5.3 Understand the different application areas for text mining 5.4 Know the process of carrying out a text mining project 5.5 Appreciate the different methods to introduce structure to text-based data 5.6 Describe sentiment analysis 5.7 Develop familiarity with popular applications of sentiment analysis 5.8 Learn the common methods for sentiment analysis 5.9 Become familiar with speech analytics as it relates to sentiment analysis

6.1 Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics 6.2 Understand the basic concepts of analytical decision modeling 6.3 Understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support 6.4 Describe how spreadsheets can be used for analytical modeling and solutions 6.5 Explain the basic concepts of optimization and when to use them 6.6 Describe how to structure a linear programming model 6.7 Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking 6.8 Understand the concepts and applications of different types of simulation 6.9 Understand potential applications of discrete event simulation

复旦大学：《管理信息系统 Management Information Systems》（英文版）课程PPT_PART I Introduction to the Concept of Information Systems in Business Session 5 Summary of IS Concept and Application Framework

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（PPT课件，第3版）Chapter 04 Data Mining