The University of North Carolina at Greensboro
Bryan School of Business and Economics
Department of Information Systems and Supply Chain Management
ISM 425 Business Analytics
Class Room:
Class Time:
Instructor:
E-mail:
Office:
Office hours:
Course website:
SOEB 222
M/W 2:00-3:15pm
Dr. Xia Zhao
x_zhao3@uncg.edu
Bryan 422
M 3:30-4:30pm or by appointment
Canvas.uncg.edu
Catalog Description:
Introduction to business analytics including concepts and techniques which help gain insights that
inform business decisions using data.
Course Description:
In the era of e-commerce and information economy, enormous amounts of data have been
generated from business transactions, networked sensors, social networking activities, etc. Datadriven decision-making has been used across many functional areas in businesses such as
targeted advertising, personalized recommendation, supplier/customer relationship management,
product design, credit scoring, fraud detection and workforce management. It is critical for
businesses to acquire data analytics capability so they can gain insights into consumer behavior
and industry trends. Instead of taking guessing out of or betting on business decisions, the ability
of capturing and analyzing data allows firms to make informed business decisions.
As data brings enormous opportunities, businesses are also facing tremendous challenges in
leveraging the data to generate values. This purpose of this course is to introduce students to
theories and current practices in business analytics and explain how data-driven business
analytics technologies can help in many important business applications. This course provides a
comprehensive exploration of a variety of data analytics techniques through hands-on exercises.
Upon completion of this course, students will be able to:
1. Demonstrate an understanding of the key theories, concepts, and models of business
analytics;
2. Identify business analytic opportunities that create value in traditional and new industry;
3. Prepare and formulate data collection, sampling, preprocessing;
4. Identify different business analytics methodologies;
5. Apply data analytics techniques to formulate and solve various business problems.
Texts and Course Materials:
Galit Shmueli, Nitin R. Patel, Peter C. Bruce. Data Mining for Business Intelligence: Concepts,
Techniques, and Applications in Microsoft Office Excel with XLMiner, 2nd Edition, Wiley, 2010.
ISBN:
978-0-470-52682-8.
www.dataminingbook.com
Accompanying
datasets
are
available
from
Additional readings will be posted on course website.
Required Software
The textbook comes with the XLMiner software (6-month license). Each textbook has an access
code for the software which can be downloaded from the web. In addition to the copy of the
software coming with in the book, I have arranged for a 140-day classroom license. You may
download the software from the Internet and obtain a license key using the information that I will
provide in class.
Tableau is a business intelligence software that allows you to interactive visualizations. It is
available for free to students.
Evaluation and Grading:
The course will be letter graded. A student’s final grade will depend on the quality of the project
components.
Individual assignments
Midterm exam
Group project
Final exam
30%
20%
30%
20%
100%
The grade scale is based upon percent of points earned, and is as follows:
87-90%=B+
77-80%=C+
67-70%=D+
93-100%=A
83-87%=B
73-77%=C
60-67%=D
90-93%=A80-83%=B70-73%=CBelow 60%=F
Keep a record of all points possible and earned on each. This will make it easy for you to
determine your exact grade status throughout the course. They may also be needed to resolve any
discrepancies in your record.
Teaching Methods
This course blends lectures, individual assignments, class discussion, group project, midterm and
final exam.
Individual Assignments
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Assignments are due by the start of class as indicated in the schedule. Assignments turned in
late will be assessed a grading penalty. Unless waived or reduced by the instructor, late
assignment will be marked 20% lower for each day late.
Group Project
Each student is required to join a group of three individuals to work on a project. More details
about the project will be given during the course.
Mid Term and Final Exams
Midterm and final exams are required for the course.
Academic Integrity Policy
Each student is required to sign the Academic Integrity Policy on all major work submitted for
the course. The Academic Integrity Policy can be found at:
http://sa.uncg.edu/handbook/academic-integrity-policy/.
Faculty and Student Guidelines
The faculty and students in the course are expected to adhere to the faculty student guidelines
stated at the following web page: http://www.uncg.edu/bae/faculty_student_guidelines.pdf
Attendance Policy
Each student is responsible for all the information and announcements that are made in class. Poor
attendance causes poor performance in this course. Any student missing the first class without
notifying the instructor will be administratively dropped from the course. Any student missing
more than three classes (excused or not) may have their grade dropped by a letter grade.
UNCG rarely closes for inclement weather. The radio and TV stations will have the closing
notification by 6:30 am. You may also call 334-5000 for a message related to weather closings.
These messages are updated hourly.
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