City University of Hong Kong. Information on a Course offered by Department of Information Systems with effect from Semester B in 2013 / 2014

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1 City University of Hong Kong Information on a Course offered by Department of Information Systems with effect from Semester B in 2013 / 2014 Part I Course Title: Course Code: Course Duration: Business Intelligence and Analytics IS4834 One Semester (13 weeks) Credit Units: 3 Level: Medium of Instruction: Prerequisites: (Course Code and Title) Precursors: (Course Code and Title) Equivalent Courses: (Course Code and Title) Exclusive Courses: (Course Code and Title) B4 English Part II 1. Course Aims This course aims to Introduce the major concepts of and data mining; Provide knowledge about how to provide business solution using business intelligence techniques; Explain the roles that software tools and applications play in and data mining; Give students an overall understanding of the classes of algorithms and the best practices for building projects successfully. 1

2 2. Course Intended Learning Outcomes (CILOs) Upon successful completion of this course, students should be able to: No. CILOs Weighting (if applicable) 1. Recognize the need for to 2 support business. 2. Apply the concepts and techniques of business 3 intelligence and analytics in business practice. 3. Apply information technologies for data 3 mining. 4. Analyze the requirements for support and identify tools and techniques for data mining in order to create innovative solutions. (3: Relatively most focused ILOs; 2: moderately focused ILOs; 1: less focused ILOs) DEC Dimensions (Attitude/ Ability/ Accomplishments) 2 Ability, Accomplishments 3. Teaching and Learning Activities (TLAs) (Indicative of likely activities and tasks designed to facilitate students achievement of the CILOs. details will be provided to students in their first week of attendance in this course) Final Lecture: Laboratory/Tutorial: 26 hours 13 hours TLA1: Lecture Concepts and applications of information technology in the context of business intelligence and data mining are explained by instructor. TLA2: Laboratory/Tutorial During laboratory/tutorial sessions, the following activities are used to reinforce the learning and practice of various and data mining techniques learnt in lectures: Exercises: Hands-on activities using database systems, SQL and software to perform data mining techniques of classification, clustering, and association rule mining. Discussion: Discussion of various concepts learnt in lectures, and exemplified with exercise to demonstrate the applicability of various techniques in business intelligence Presentations: Members of project team will make presentation of their project work, and the rest of the tutorial group and the instructor will comment and offer suggestions for improvements. 2

3 TLA3: Project Students will have to complete a group project requiring them to adopt business intelligence and data mining technology to solve business ILO No. TLA 1: Lecture TLA 2: Laboratory/Tutorial CILO 1 2 CILO CILO CILO (1: Indirectly Supporting ILO; 2: Directly Supporting ILO) TLA 3: Project Hours/week (if applicable) 4. Assessment Tasks/Activities (Indicative of likely activities and tasks designed to assess how well the students achieve the CILOs. Final details will be provided to students in their first week of attendance in this course) AT1. Lecture, Laboratory Exercises and Participation (20%): Each seminar and laboratory may consist of exercises, quizzes, small group discussions, self reflection, or student presentations to assess students abilities to apply their skills. AT2. Group Project (30%): A group project, which includes a project report and presentation, will be allocated to let students apply business intelligence and data mining concepts and technologies to solve business AT3. Examination (50%): A 2-hour written examination to assess students competence of the taught subjects. ** Students must pass both coursework and examination in order to get an overall pass in this course. ** ILO No AT1 (20%) AT2 (30%) AT3 (50%) CILO CILO CILO CILO (1: Indirectly Supporting ILO; 2: Directly Supporting ILO) 5. Grading of Student Achievement: Standard Grading pattern (A+, A, A- C-, D, F) ILO Excellent Good Adequate Marginal CILO1 all key concepts of deep understanding of their importance to business. all key concepts of general understanding of their importance to business. most key concepts of basic understanding of their importance to business. some key concepts of business intelligence and data mining; and minimal understanding of their importance to business. 3

4 CILO2 CILO3 CILO4 Evaluate accurately the Compare and evaluate accurately and profoundly about distinguished impact of technologies for and effectively formulate and well-rounded identifying most existing Evaluate reasonably the Evaluate reasonably and sensitively about the distinguished impact of technologies for well-rounded identifying some existing Evaluate modestly the Evaluate modestly and objectively about the distinguished impact of technologies for major requirements of reasonable degree of identifying reasonable existing Evaluate minimal the data warehouse. Evaluate with minimal sensitive reflection about the distinguished impact of technologies for most important limited identifying necessary existing data mining tools and technique for Part III Keyword Syllabus Management support and ; Data warehousing; Mining and visualization; Mining from data warehouses; Regression analysis; Business intelligence for customer relationship ; Customer profiling; Application of decision trees; Clustering, neural networks, and market basket analysis to ; Business analytics. Recommended Reading Text(s) L. Langit, K.S. Goff, D. Mauri and S. Malik, Smart Business Intelligence Solutions with Microsoft SQL Server 2008 (PRO-Developer), Microsoft Press, Brian Larson, Delivering Business Intelligence with Microsoft SQL Server 2008, McGraw-Hill, Olson, D. and Shi, Y., Introduction to Business Data Mining, McGraw-Hill,

5 Turban, E. and Aronson, J., Decision Support Systems and Intelligent Systems, 6 th edition, Prentice-Hall, Lewis, W. J., Data Warehousing and E-Commerce, Prentice Hall,