Syllabus
Here is the Syllabus of MIS2502 Data Analytics Section. (as of 8/17/2019)
Introduction
The course provides a foundation for designing database systems and analyzing business data to enhance firm competitiveness. Concepts introduced in this course aim to develop an understanding of the different types of business data, various analytical approaches, and application of these approaches to solve business problems. Students will have hands-on experience with current, cutting-edge tools such as MySQL and R.
Learning Outcomes
- Articulate the key components of an organizations’ information infrastructure.
- Create data models based on business rules.
- Create a transactional database from a model using SQL.
- Create an analytical data store by extracting relevant data from a transactional database.
- Perform extract, transform, load (ETL) functions such as data sourcing, pre-processing, and cleansing.
- Discover trends in analytical data stores using the data mining techniques of clustering, segmentation, association, and decision trees.
Prerequisites
Grade of C or better in MIS2101.
Evaluation
|
Item |
Percentage |
| Exams (3) | 60% |
| Assignments (10) | 30% |
| Group project (1) | 5% |
| In-class activities | 5% |
Grading
| Scale | |||
| 94 – 100 | A | 73 – 76.99 | C |
| 90 – 93.99 | A- | 70 – 72.99 | C- |
| 87 – 89.99 | B+ | 67 – 69.99 | D+ |
| 83 – 86.99 | B | 63 – 66.99 | D |
| 80 – 82.99 | B- | 60 – 62.99 | D- |
| 77 – 79.99 | C+ | Below 60 | F |
Exams
There will be three exams during the semester. Tentative exam schedules are available below.
- Exam 1: 10/1 during class time
- Exam 2: 10/31 during class time
- Exam 3: 12/5 during class time
PRO Point Requirement (MIS Majors Only)
All BBA in MIS majors must have 200 Professional Achievement (PRO) points by the end of this course in order to receive a grade. If you do not have 200 points by the of the term, you will receive an incomplete, which will remain in place until you reach the required number of points.
Assignments
There will be nine assignments. All assignments should be submitted via Canvas before due date. They are to be done individually and should represent your own work. If you need help, you may consult with your instructor or the ITA for the course.
Late Assignment Policy
All assignments will be assessed a 50% penalty (subtracted from that assignment’s score) for the first day (i.e. 24 hours) they are late. No credit will be given for assignments turned in more than 24 hours past the deadline.
Please note:
- Equipment failure is not an acceptable reason for turning in an assignment late.
- In case the Canvas submission link does not work, you must send the submission to the instructor’s email by the due date.
- For the assignment to be considered “on time,” you must attach all necessary files specified in the assignment instructions by the due date. For any revisions or additional documents received after the due date, the usual late penalty applies.
Group Project
There will be a group project released later in the semester. Students will be asked to analyze a data set from the Temple Analytics Challenge (http://ibit.temple.edu/analytics) and create a visualization of their findings. Students should work in groups of 2 to 4. Members in the same group will receive the same grade.
In-Class Activities
In-class activities are very hands on in nature, where students will be expected to work with various examples and data sets based on instructions and class discussions.
After we complete the in-class activities, you are required to submit your solutions through Canvas by the end of the class unless otherwise notified.
You are allowed to miss two submissions for in-class activities. Deliverables from in-class activities will be graded by success or fail. Missed or late submissions will receive a zero (fail) grade. Equipment failure is not an acceptable reason for turning in a deliverable late.
Class Participation
Participation: I strongly encourage your active class participation and discussion. Involvement during class is also important. Being present in class to ask and answer questions is essential to the learning process. Don’t feel shy to speak up, ask questions or answer them. All students are expected to come prepared for the class and volunteer answers. I may also “cold call” students in class. However, note my policy is not to cold call students who are sitting in the front row. If something prevented you from being prepared for class on a particular day, you are invited to sit in the front row.
Classroom Etiquette
The environment you and your fellow students create in class directly impacts the value gained from the course. To that end, the following are my expectation of your conduct in this class:
- Arrive on time and stay until the end of class.
- Turn off cell phones, pagers and alarms while in class.
- Limit the use of electronic devices (e.g., laptop, tablet computer) to class-related usage such as taking notes. Restrict the use of an Internet connection (e.g., checking email, Internet browsing, sending instant messages) to before class, during class breaks, or after class.
- During class time speak to the entire class (or breakout group) and let each person “take their turn.”
- Be fully present and remain present for the entirety of each class meeting.
Plagiarism and Academic Dishonesty
Plagiarism and academic dishonesty can take many forms. The most obvious is copying from another student’s exam, but the following are also forms of this:
- Copying material directly, word-for-word, from a source (including the Internet)
- Using material from a source without a proper citation
- Turning in an assignment from a previous semester as if it were your own
- Having someone else complete your homework or project and submitting it as if it were your own
- Using material from another student’s assignment in your own assignment
If you use text, figures, and data in reports that were created by someone other than yourself, you must identify the source and clearly differentiate your work from the material that you are referencing. There are many different acceptable formats that you can use to cite the work of others (see some of the resources below). You must clearly show the reader what is your work and what is a reference to somebody else’s work.
Plagiarism and cheating are serious offenses. Penalties for such actions are given at my discretion, and can range from a failing grade for the individual assignment, to a failing grade for the entire course, to expulsion from the program.