College of Business
BA483 Business Analytics


Instructor: Bin Zhu, College of Business

BA 483 Business Analytics

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Overview: BA483 is about how organizations can successfully “collect, evaluate and apply information” for better decision making. Emerging technologies such as transaction processing systems, RFID, weblogs, social networks, website usage, and online communities have the potential to reveal market trends, suppliers' preferences, and competitors' next moves. The success of an organization largely depends on its ability to take advantage of those data sets that are already available to it. The class starts with basic IT strategy concepts for the identification of the opportunities for BI solutions, and ends with hands-on experience using Business Intelligence tools to implement such solutions. It also covers the application of Business Intelligence tools to address challenges in various aspects of organizations, including customer relationship management, internet marketing, supply chain management, information security, and human resource management.

You do not need strong technical skills in statistics or programming to benefit from the course. The material is delivered in an intuitive manner, aiming to make you a better decision maker with the ability of selecting appropriate analytic tools for specific managerial issues. After completion of the course, you should possess valuable analytical skills that should provide a competitive edge in any contemporary workplace. In particular, students seeking careers in IT services, analytics, marketing, and strategic planning may find this class helpful. The class project is designed to help you become a business intelligence gatherer in your chosen field


Prerequisites: BA 371 and BA 479 and senior standing.

Course Type: Lecture

Course Credit: 4

Course Learning Outcomes

Students who successfully complete BA483 can:

  • Identify the business and technical requirements for a Business Intelligence solution
  • Detect business intelligence service opportunities that exist in today's data-rich environment
  • Plan Business Intelligence operations and their management
  • Understand analytical methods of classification, prediction, reduction and exploration
  • Integrate information capturing, representation, analysis, and presentation methods to support key organizational decisions
  • Map business issues with Business Intelligence techniques
  • Implement major techniques using Excel add-ins

Group Project

The group project will be 30% of your grade. Each group is expected to identify and to execute a business intelligence project that applies the data capturing and analysis techniques covered in this class. The key tasks are:
• Identify a business problem or a series of interesting questions that are strategically important to the industry selected by your team
• Identify sources of data that could potentially be useful in addressing your questions
• Pre-process – clean, validate and visualize your data
• Develop your model considering alternative techniques, selecting the most appropriate one in the process.
• Interpret your results and write a final report including an executive summary of your findings.
• Discuss your plan of implementing the BI solution. How can organizations benefit from the BI solution you developed?
• Prepare a 10-15 minute professional presentation for the last class meeting

Course Information

OSU 'No Show Drop' rule

Note that for this course the OSU 'No Show Drop' rule will be strictly enforced. This rule: Academic regulations AR 9§b reads as follows:

"If it is anticipated that the demand for enrollment in a given course will exceed the maximum number that can be accommodated, the department offering the course may designate it in the Schedule of Classes with the code "NSHD" (no-show-drop). A student who is registered for such a course who attends no meetings of the course during the first five school days of the term will be dropped from the course by the instructor, unless the student has obtained prior permission for absence. If such action is taken, the instructor will send written notice through the department to the Registrar’s Office, which in turn will notify the student that the course has been dropped from his or her schedule. Students should not assume they have been dropped unless they receive notification from the Registrar’s Office. No fee will be charged."

Email: Note that if you email your instructor from any off-campus email account/server; e.g., gmail or hotmail, there is NO GUARANTEE(!!) that your email is delivered or that you receive a reply. Bypassing or not using the OSU campus email facilities carries 'no delivery' risks for which you are responsible.

Academic Dishonesty: The penalty for academic dishonesty is severe. Any student guilty of academic dishonesty may be subject to receive a failing grade for the exam, assignment, quiz, or class participation exercise as deemed appropriate by the instructor.  Students are expected to know and understand these policies and regulations.  If there is any doubt about their meaning and interpretation please ask for an explanation. Direct or indirect use of student work from previous terms to complete your exams or assignments is a violation of academic honesty. If you turn in all or part of someone else's work as your own or allow someone else to turn in your work as theirs, then you have committed a violation of academic honesty and will be dealt with in accordance with regulations of the University.  If you would like to know more about how this works, I recommend reading more about the University's Office of Student Conduct.

Behavior in class: Behavior in class should be professional at all times. People must treat each other with dignity and respect in order for scholarship to thrive. Behaviors that are disruptive to learning will not be tolerated and may be referred to the Office of the Dean of Students for disciplinary action.  Please keep the side conversations to a minimum and turn your cell phones off during class. No headphones may be used during class. If you need to leave during class, please exit quietly. Computer/Cell Phone usage in class should support the learning environment, such as reviewing the lecture slides, taking notes, etc. Please do not distract yourself, or others by surfing outside web sites, carrying on electronic conversations with someone outside of class, etc.

Discrimination and harassment: Discrimination and/or harassment will not be tolerated in the classroom. In most cases, discrimination and/or harassment violates Federal and State laws and/or University Policies and Regulations. Intentional discrimination and/or harassment will be referred to the Affirmative Action Office and dealt with in accordance with the appropriate rules and regulations.

Students with Disabilities: Accommodations are collaborative efforts between students, faculty and Disability Access Services (DAS). Students with accommodations approved through DAS are responsible for contacting the faculty member in charge of the course prior to or during the first week of the term to discuss accommodations. Students who believe they are eligible for accommodations but who have not yet obtained approval through DAS should contact DAS immediately at 737-4098.

Syllabus:  This syllabus and schedule are a guide, not a contract. They will change during the term as I attempt to provide the most compelling and useful learning experience possible.   If things do not make sense, please talk with me. As changes are made, I will announce them in class. You should check the syllabus at least once a week for course updates.  Not reading the syllabus does not constituent a valid excuse for missing a milestone.

Texts & Supplemental Material

Title: Data Mining for Business Intelligence, Concepts, Techniques, and Applications, Second Edition
Author: Galit Shmueli, Nitin R. Patel, Peter C. Bruce

ISBN 978-0-470-52682

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner


Course Evaluation -- Grading

Announcements: I will use Blackboard to communicate announcements and changes in the course schedule or course assignments.  Students are expected to check Blackboard and email daily.

Assignments:  The class scheduleindicates the required reading and any deliverables due for that day. Class notes are also available.  Late assignments will be deducted 10% and assignments that are more than 2 days late are not accepted.

Midterm :The date posted in the syllabus for the midterm will not be altered to accommodate your schedule. It is your responsibility to be at the stated location to take the exam.

Group Presentations:Each group will be assigned articles to present at the beginning of each class and 10% of your grade comes from the presentation. I will have a set of questions for the class to discuss after your presentation. And your presentation grade will be decided by your peers based on their assessment of how your presentation helps them participate in the class discussion afterward.

Assignments & Homework:  Start your assignments early! Frequently, students that wait until the day prior end up getting stuck on some technical point they do not know how to resolve and fail to complete the assignment on time. Start assignments as soon as they are discussed in class so that you can get assistance if needed and complete the assignment on time. Ask questions in class if you are unsure of how to complete somethin.

Group Project: Please see above description about the group project.

Peer's Evaluation:35% of your grade depends on how your team performs. Being able to productively work with people is an important career skill for you to have. While most students in BA483 receive the team grade as their project grade, that will not be the case for everyone. Some team members contribute relatively little and some make contributions which other team members may actually regard as negative.  On the last day of class, after the final presentation, you will fill out a peer evaluation form to evaluate the contribution of your team members, including yourself. Each team member will be categorized as a regular contributor, a greater than regular contributor, or a less than regular contributor. The regular contributors get the team's grade as their project grade, while the greater contributors will receive an upward adjustment of 1/2 to a whole letter grade for their project grade based on the peer evaluation. The less than regular contributor will be similarly downgraded.

Course Grades:   Letter grades will be assigned according to the number of points accumulated on activities and exams. The following table indicate grade contributions.


Percentage of total

Homework 1 Prediction 10%

Homework 2 Classification


Homework 3 Association Rules and Clustering 10%

Team Presentation


Class Participation 10%

Midterm I


Midterm II 12.5%

Team Project




Participation: Your default class participation grade is 80/100. You can increase this grade by coming to class prepared, answering and asking questions in class, ,  e-mailing me interesting class-related articles that you want to share with the class, etc.. Your participation grade will be negatively affected by  being late, absent, disruptive, by sleeping, or by not participating in discussions.

Grades will be assigned based on the following scale:






> 93%