Type of Credit: Elective
Credit(s)
Number of Students
|
We are living in the era of big data. Technologies enable companies to collect tremendous volumes of information; however, many firms complain that they are drowning in a sea of data. Indeed, many items of data are meaningless until they have been analysed by appropriate techniques that may lead to important business insight. Business analytics has thus become one of the most important skills that empower organisations to achieve timelier, and more perceptive decisions to create business value and growth.
This English-taught course is designed to provide students with the fundamental concepts and applications necessary to understand the role of business analytics in modern organizations. The students will acquire a range of data mining, visualization, and analytical techniques to facilitate the analysis of enterprise big data (via software tools), and will uncover new information to support business decision-making.
Overall, the course aims to provide you with a solid foundation in the ‘basics of analytics’ and ‘SAS’. We are not going to focus on the derivation of mathematical formulas or advanced SAS code development. Instead, we will use a number of real-life examples (business scenarios) with provided data and SAS code to enable you to practice the process of data analytics. Thus, there is no prerequisite for taking this course.
Note: Students who would like to learn advanced analytic techniques such as optimization, machine learning, and decision trees are not recommended to register for this course. There will only be a brief introduction to these topics, since such techniques require students to have strong quantitative abilities.
Course Arrangement:
Note: a. The download and installation process can take several hours, depending on your broadband speed. b. SAS 9.4 is exclusively compatible with Windows machines (for Win 64x). Mac users, however, can opt for the Free SAS Studio, which is available online, though there might be a slight difference in the interface. The class will cover the features of both versions. (Note: Windows users can also seamlessly use the SAS Studio without encountering any issues.)
|
能力項目說明
|
Course Objectives:
Learning Outcomes By the end of this course, students will be able to:
|
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
|
The above schedule is subject to adjustments based on actual circumstances, with the latest version taking precedence. In case of any changes, notifications will be provided before the class, so please stay informed. Lecture structure: - first part: 18:00-19:20 | 20 min break | second part: 19:40-20:50 | close: 20:50-21:00
Independent Study: There will be TWO independent study weeks: On May 30, 2024, you will be required to review all the concepts we have discussed and prepare for your group presentation; and on June 20, 2024, you will be required to review your final report with your group members, and list each member’s contribution in the final report.
Term Project (group-based with consideration of individual participation): Teams will apply the business analytics tools learned in this course to a chosen topic (e.g. the business issues in a chosen industry and how to analyze the collected data to develop recommendations) in order to complete a group report and group presentation. The project format and outline will be introduced in the lecture. Besides, the add and drop period ends in Week 2. Accordingly, you will join the belonging group in Week 3. You are free to select your team members, although please remember that the maximum group size is 3 people. Please inform me in writing with your preferred team members' names before the end of the Week 3 lecture. You will be assigned the group ID in the following week.
1. Final Presentation (Presentation on June 13, 2024; Presentation slides due 12:00 noon, June 11, 2024) Each team should prepare a 20–30 minute presentation that introduces your project and analysis. You will receive comments/feedback that can assist you in completing the final report.
2. Final Report (Final Report due 12:00 noon, June 21, 2024) Your group report will contain 2,500 words (+/- 10%), excluding tables, figures, and references, and should be written in English. The report requires a cover page that includes the title of your study, and the names of all those who have participated (no abstract is necessary). You should reference your sources and articles following the Harvard referencing guidelines, and you MUST give careful consideration to the issue of plagiarism. Besides, late submissions will incur a 3% grade penalty per weekday (excluding holidays) if the submission is late.
Note: An additional guideline on how to write a quantitative report will be taught after the “Correlation and Linear Regression” session.
Homework (individual-based): There will be homework assigned after each session. You will either be required (i) to write a short paragraph describing what you have learned in each class; or (ii) to complete an exercise relevant to the content we have covered in that lecture. For each piece of homework that you submit on time, you will receive one point (e.g., 15 points = 15 weeks of submitted homework).
|
|
Textbook
Additional Recommended Reading: