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ITIS5431

Business Analytics Methods

November 18, 19, 25, 26, 2023

Course Description: Tools for data analytics; analyzing data beyond statistics; data mining and predictive modeling; time series analysis and forecasting; neural networks algorithms in business analytics.

Learning Objectives: Introduction of the role of data mining in current business organizational strategy. This course will provide an overview of the different Analytics approaches by situating data mining in organizational and commercial context. Students will be expected to understand and communicate the business value of the business analytics and the merits of different analytical approaches.

The students will also participate in exercises in data preparation and profiling and hands on predictive modelling using a variety of data analytic techniques and practices using a SAS Enterprise Guide.

Course Delivery:  Students will be required to watch the lecture and technical “How To” videos that will be provided on Brightspace. This can be completed asynchronously on the student’s time. There will be technical drop-in sessions held at a scheduled Zoom call whereby students can log in to the zoom session if they need assistance completing the assignments or have questions on the lecture videos. These sessions will be recorded and posted on Brightspace for students who cannot attend the sessions.

Course Prerequisites:  The prerequisite for this course are: BUSI 5801 (or equivalent).

Textbook(s):  There will be one book  used for ITIS5431 & ITIS5432. These are not mandatory, and students can complete the course using lecture slides.

· (Optional) Business Analytics Using SAS® Enterprise Guide® and SAS® Enterprise Miner®: A Beginner’s Guide. Copyright © 2014, SAS Institute Inc., Cary, NC, USA

Drop Course Policy:

The deadline for academic withdrawal is the last day of classes (each term).

Grading Scheme:   2 Hands on Assignments     50%

Take Home Final Exam  50% 

TOTAL 100% 

Course Software: SAS Enterprise Guide will be used to complete the course assignments. It is highly recommended that students familiarize themselves with SAS as much as possible before the assignments are distributed.  For assignments, the course will use the SAS for Academics or the SAS VDI environment on Carleton’s mydesktop platform. Instructions on how to access this portal will be given on the Brightspace site.

Assignments: Students will be given two assignments for completion. SAS Enterprise Guide will be used to complete the assignments. Students may work in groups to complete the assignments; however, each student must prepare and submit their own assignment. Both assignments must be submitted through Brightspace at a time to be determined after Lecture 1.

Final exam date:  A final take home written exam will be made available on Brightspace on December 1 2023. The exam will be submitted via Bright Space at a time to be determined. Students must complete the take home exam individually. The exam may ask the students to demonstrate their ability to manipulate and analyze datasets, SAS Output and or Short Answer Questions.

Preparation and participation: Students are expected to have read the readings assigned. This will help the students understand the context of the analytical method(s) that will be covered in class.

Missed assignments and deferred examination: All assignments and cases not submitted by the specified times will be assigned a mark of zero.

Deferred Final Examination:

Students unable to write a final examination because of illness or other circumstances beyond their control must contact the instructor and the MBA office in writing to request a deferred exam. Permission may be granted when the absence is supported by a medical certificate and or appropriate document/s to support the reason for the deferral.

Course Schedule

Policy on Mobile Devices

The use of mobile devices IS NOT PERMITTED in this class.  It is disruptive to the instructor and class members. If you carry such a device to class, please make sure it is turned off.  If an emergency situation requires you to keep it turned on, please discuss this with your instructor prior to class.

Group Work

The Sprott School of Business encourages group assignments in the school for several reasons. They provide you with opportunities to develop and enhance interpersonal, communication, leadership, followership and other group skills. Group assignments are also good for learning integrative skills for putting together a complex task. Your instructor may assign one or more group tasks/assignments/projects in this course.  

Before embarking on a specific problem as a group, it is your responsibility to ensure that the problem is meant to be a group assignment and not an individual one.

Academic Integrity

Violations of academic integrity are a serious academic offence. Violations of academic integrity – presenting another’s ideas, arguments, words or images as your own, using unauthorized material, misrepresentation, fabricating or misrepresenting research data, unauthorized co-operation or collaboration or completing work for another student – weaken the quality of the degree and will not be tolerated. Penalties may include expulsion; suspension from all studies at Carleton; suspension from full-time studies; a refusal of permission to continue or to register in a specific degree program; academic probation; and a grade of Failure in the course, amongst others.  Students are expected to familiarize themselves with and follow the Carleton University Student Academic Integrity Policy which is available, along with resources for compliance at: http://www2.carleton.ca/sasc/advisingcentre/academic-integrity/. 

Course Sharing Websites

Student or professor materials created for this course (including presentations and posted notes, labs, case studies, assignments and exams) remain the intellectual property of the author(s). They are intended for personal use and may not be reproduced or redistributed without prior written consent of the author(s).