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Viewing: BUS 458 : Analytics: From Data to Decisions

Last approved: Thu, 23 Jun 2016 08:01:57 GMT

Last edit: Wed, 20 Apr 2016 17:50:55 GMT

Change Type
Minor
BUS (Business Management)
458
032246
Dual-Level Course
No
Cross-listed Course
No
Analytics: From Data to Decisions
Analytics: Data to Decisions
Poole College of Management
Business Management (20BUS)
Term Offering
Fall and Spring
Offered Every Year
Previously taught as Special Topics?
No
 
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded with S/U option
3
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture3.0
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Tonya Balan
Teaching Professor

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture3030Non/a
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote
Prerequisite: BUS 443
Is the course required or an elective for a Curriculum?
No
Students will develop and apply their data analytics skills by analyzing case studies built around real business problems and real data. Case studies are designed around the full analytics lifecycle which encompasses the business problem, data, analysis, and decision. Students will learn to identify and explain business problems that can be addressed with analytics. They also will learn to determine which analytic methods are best suited to solve particular problems and will evaluate the impact of applying analytic methods. Finally, they will learn to explain the results of an analytic model and how those results impact the business "bottom line.

No

Is this a GEP Course?
No
GEP Categories

Humanities Open when gep_category = HUM
Each course in the Humanities category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

Current resources allow offering this course.

Student Learning Outcomes

At completion of this course, students will be able to:



  1. Examine data and identify patterns and trends;

  2. Interpret statistical results;

  3. Communicate results using visual analytic techniques;

  4. Develop business segmentation strategies using data analytics skills.


Evaluation MethodWeighting/Points for EachDetails
Written AssignmentCourse Grading:

Homework Assignments 1-5 10% (each 2%)
Case Reports 90% (each 18%)
see weighting
TopicTime Devoted to Each TopicActivity
BUS 458 Class Meeting ScheduleClass Meeting Topic Readings Assignment DueMeetings 1 - 6 Case 1: Data Visualization-Discussion of business problem-Choosing the best visualization-Identifying patterns and trends-Creating data-driven recommendations for the business Clear Storytelling Boosts the Value of Analytics Meeting 3: Homework 1Meeting 6: Case Report 1Meetings 7 - 12 Case 2: Linear Regression - Discussion of business problem- Dealing with messy data- Iterative model building- Interpreting the results Finding the Gold in Your Data: An Overview of Data Mining Meeting 9: Homework 2Meeting 12: Case Report 2Meetings 13 - 18 Case 3: Binary Response Model-Discussion of business problem-Choosing the best model-Classifying new observations-Developing business segmentation strategies A Data Driven Approach to Predict the Success of Bank Telemarketing Meeting 15: Homework 3Meeting 18: Case Report 3Meetings 19 - 24 Case 4: Analytic Decision Management-Explore the 4 facets of the analytic life cycle-Prepare and explore data-Identify appropriate statistical method-Create business recommendation-Generate plan for deploying model into operations Competing on Analytics Meeting 21: Homework 4Meeting 24: Case Report 4 Meetings 25 - 30 Case 5: Developing an Analytics RFP-Write a clear statement of a business problem-Identify data that could be used to solve it-Specify statistical methods that should be used-Create a template for presentation of results- Develop a plan for implementation Model Deployment: The Moment of Truth Meeting 27 Homework 5Meeting 30: Case Report 5
SVHoward: Memo received attached, semester offering changed as minor action in CIM.
Key: 8048