INFO361-14S2 COURSE OUTLINE. Special Topic: on Business Intelligence Systems in Organisations. College of Business and Economics

Transcription

1 INFO361-14S2 College of Business and Economics COURSE OUTLINE Special Topic: on Business Intelligence Systems in Organisations Second Semester Department of Accounting & Information Systems Course Supervisor Dr Stephen Wingreen, Phone (or Ext 6651) 14

2 PLEASE NOTE It is the student s responsibility to retain all course outlines for any future assessment by professional bodies or other institutions 2

3 INFO361-14S2 Special Topic on Business Intelligence Systems in Organisations 1. COURSE OBJECTIVES AND CONTENT In today s organisations the idea of being data rich and information poor is a common theme. More than ever before, organisations are able to produce and store massive amounts of data (in proportion to the size and complexity of their operations). Yet many fail to turn such data into useful information that can inform practice and support strategic initiatives. To address this problem, organisations are investing in business intelligence systems that can harness, store, connect and model data in ways that provide insights (i.e. business intelligence ), enable new business opportunities, and help employees make strategic decisions that can improve operations, growth and competitive advantage. Business Intelligence (BI) Systems are information systems that use various technologies, processes and applications to analyse operational, social and other data (including structured and unstructured, and internal and external data) and identify patterns, trends and relationships that can be used to support an organisation s business objectives. The term business intelligence describes both the product and the process by which organisations obtain, analyse and distribute business intelligence. This Special Topic course on Business Intelligence Systems in Organisations discusses key aspects related to BI systems and technologies and their application in organisations. The course also covers topics in data warehousing, predictive analytics, data visualisation, data mining (including text and web mining), and emerging trends in BI. A mix of theory and practice with real-world cases to demonstrate key principles of BI are important aspects of this course. These are aimed at helping students to understand key concepts, and develop analytical and problem-solving skills related to BI solutions. In this course the concepts of BI are approached from two perspectives - managerial and technical. The managerial perspective is emphasised in the textbook and through research and the use of case studies. The technical aspects are also introduced in the textbook, and through readings and case studies; students will also be able to gain practical knowledge and hands-on experience with using BI systems and supporting tools. At the end of this course, it is expected that students will have gained an understanding of key BI concepts and of the role and use of BI systems in organisations. More specifically, it is expected that students will be able to: 1. Demonstrate an understanding of key BI concepts, processes and technologies 2. Identify the need for and explain the use of Business Intelligence systems to support data management and decision-making in organisations. 3. To recognise and analyse business problems and opportunities related to the role of BI in organisations; select and apply suitable strategies, tools and/or techniques (e.g. in data mining/ analytics) supported by BI systems to these problems/opportunities and; make recommendations that align with the organisations context and business strategy. 4. Produce appropriate information models and reports using BI software/visualisation tools; and 5. Work as a team to perform key activities related to the analysis of a business problems and recommendation of a BI-enabled solution. 3

4 2. RELATION TO OTHER COURSES This course is a third-year component of the ACIS department's Information Systems (IS) stream. It discusses key developments in the role and use of information technology to support business intelligence and decision-making in organisations. INFO361 builds on concepts covered in other IS courses (e.g. INFO123, INFO203 and INFO233) as these relate to the management and use of data and information to support decision-making in organisations, including analysis of information needs, decision support /business intelligence systems, and databases and data /knowledge management. Complementing other courses and programs within the B.Com degree, INFO361 will provide a good start in recognising opportunities for and understanding the use of BI systems in organisations. Besides being a useful course for IS majors, the concepts covered in INFO361 are also highly relevant to those interested in career paths that emphasise data-driven decision-making and strategy development with fields such as healthcare, finance, and marketing expected to be the main recruiters. 3. COURSE REQUIREMENTS and ASSESSMENT Prerequisites: The prerequisite for this course is Subject to approval by the HOD of ACIS. The criteria that will be used for this year s occurrence of INFO361-13S2, by the HOD are Prerequisites: (1) INFO123; and (2) 30 points at 200-level from any course on the Commerce Schedule Recommended Preparation: STAT101 (or equivalent) Lectures: Two hours per week Monday 9:00 a.m. - 11:.00 a.m., Erskine 244 Tutorials: There will be a 1-hour tutorial session scheduled in most weeks from 3:00 p.m. - 4:00 p.m. in Law 110. Tutorials are primarily aimed at giving students an opportunity for hands-on experience in using BI technologies. Students are strongly advised to attend these sessions. Project Students will prepare a term project consisting of a "portfolio" of five case analyses on various BI themes and techniques. For this project, students are required to acquire their own data for analysis. Data may come from any source (e.g., online sports statistics, the Teradata Network (teradatauniversitynetwork.com), online corporate financial data). Course Assessment: A summary of the assessment for INFO361 is given below. Note that all the material presented in all lectures, tutorials and referenced in the required texts, is examinable. 1. Mid-Semester Test 20% 2. Project, part1 20% 3. Project, part 2 20% 4. Final Exam 40% Students are reminded that it is their responsibility to check for clashes in exam/test times and dates for the subjects that they are enrolled in and notify the course supervisor as soon as possible. 4

5 NOTES: (a) As well as gaining an overall mark of at least 50%, there is a general departmental requirement that students are required to average not less than 45% in the invigilated component of their assessments in order to pass the course as a whole. Invigilated means formally supervised under exam conditions. In INFO361, the invigilated component of the assessments comprises the mid-semester test and the final exam. (b) The Department normally uses 50% as a cut-off point between a nominal pass or fail but may adjust the pass mark up or down to ensure fairness. Mapping of Learning Outcomes and Assessment Learning Outcomes Project Tutorials 1. Demonstrate an understanding of key BI concepts, processes and technologies 2. Identify the need for and explain the use of Business Intelligence systems to support data management and decision-making in organisations. 3. To recognise and analyse business problems and opportunities related to the role of BI in organisations; select and apply suitable strategies, tools and/or techniques (e.g. in data mining/analytics) supported by BI systems to these problems/opportunities and; make recommendations that align with the organisations context and business strategy. 4. Produce appropriate information models and reports using BI software/visualisation tools 5. Work as a team to perform key activities related to the analysis of a business problems and recommendation of a BI-enabled solution. Test/ Exam 4. TEACHING ARRANGEMENTS INFO361 is a 15-point course being offered in Semester 2 (2014). There is a significant body of theoretical and practical knowledge associated with this course. The lectures, tutorials, case study assignments and project aim both to introduce this body of knowledge, and within the limitations imposed by a teaching setting, to provide students with practical exposure to a variety of tools and techniques used to support business intelligence and key concepts that underpin the use of business intelligence systems in organisations. a) Course Lecturers: Dr. Stephen Wingreen stephen.wingreen@canterbury.ac.nz 5. TETBOOKS AND MATERIALS Regular reading is strongly advised. The content for this course will draw from a number of texts and other materials. Key titles and reference sources are listed below. The recommended text is available 5

6 through UBC and on short-term loan in the library. All other texts, reference sources and articles are available in the library on short-term loan and/or on LEARN. Note that assigned readings are examinable. Required Text: Turban, E., Sharda, R., Delen, D., and King, D. (2011). Business Intelligence A Managerial Approach, 2 nd Edition, Pearson Prentice Hall. Most of the above material is also covered in Turban, E., Sharda, R., and Delen, D. (2011). Decision Support and Business Intelligence Systems, 9 th Edition, Pearson, Chapters 5-9 Other Readings/Reference Sources: Sabherwal, R. and Becerra-Fernandez, I. (2011). Business Intelligence: Practices, Technologies and Management. Hoboken, NJ : Wiley. Evans, J. R. (2013). Business Analytics Methods, Models and Decisions, Pearson Schmueli, G., Patel, N. R., and Bruce, P.C. Data Mining for Business Intelligence, 2e, Wiley, Hoffer, J.A., Ramesh, V. and Topi, H. (2011). Modern Database Management, Pearson, Chapter 10 on Data Quality Other references, articles and handouts to be advised (See LEARN) 6. CONSULTATIONS Students encountering academic problems with INFO361 are urged to seek help first and foremost from the lecturer/course supervisor. Class Representatives Class representatives will be selected at the beginning of the course. These people will provide a valuable link between the course supervisor and the students. The representatives are expected to facilitate dialogue between the students and the course supervisor on a regular basis. This process should help to isolate and resolve potential concerns. The communications can also be used to provide positive feedback on elements of the course which are going well. 7. ALL ABOUT ASSESSMENTS, MARKING, AEGROTATS AND (NO) CHEATING etc For information on the above please use the link: and click on "ACIS Course Policies". 6

7 INFO361-14S2 Week-by-week Schedule (List and order of topics subject to change) Required Text: Turban, E., Sharda, R., Delen, D., and King, D. (2011). Business Intelligence A Managerial Approach, 2nd Edition, Pearson Prentice Hall. Week Lecture Dates Lecturer Topic Readings 1 14 July SW Course Introduction Introduction to Business Intelligence Ch July SW Foundations and Technologies for Decision Making (Tutorial) Business Intelligence/Analytics Case Study 3 28 July SW Data Warehousing Lab: Descriptive Techniques, with Excel and SPSS 4 4 Aug SW Business Reporting, Visual Analytics, and Business Performance Management Lab: Intro to Excel Analytics and SPSS 5 11 Aug SW Data Mining Lab: Data Visualization 6 18 Aug SW Mid-Term Test Lab: Regression and ANOVA Ch. 2 Ch. 3 Ch. 4 Ch. 5 N/A Mid-Semester Study Break: 23 August to 7 Sept. Classes resume Monday, 8 September 7 8 Sep SW Text Analytics, Text Mining, and Sentiment Analysis Lab: Regression and ANOVA Ch Sep SW Web Analytics, Web Mining, and Social Analytics 9 22 Sep SW Automated Decision Systems and Expert Systems Sep SW Knowledge Management and Collaborative Systems 11 6 Oct SW "Big Data" and Analytics See LEARN Ch. 11 Ch. 12 See LEARN Oct SW Emerging Trends and Future Impacts See LEARN 7