Course Syllabus

Business Intelligence and Data Analytics for MBA

Note: Please check ITM660 Google Classroom page for the latest updates and announcements.

Active participation in lab activities and successful completion of 17 lab assignments (85%) 

The lab assignments are designed to give you firsthand experience with the basic and intermediate skills for using popular business analytics tools. You will complete the lab assignments in class and upload the final files to ITM660 Google Classroom (class code is d47lb9c).

Submission of three reports on the selected lab activities (15%)

You will be asked to write three team reports on the three assignments and submit to ITM660 Google Classroom. Please note that you cannot use extra credits to make up for the missing reports. Failure to submit the following reports would negatively affect your grades from the lab assignments. Your reports should be prepared in group (2 to 3 students per group) and peer-reviewed by at least one group before submission.

  • Report I (5%): Data Visualization & KPI Dashboard Development 
  • Report II (5%): Data Mining
  • Report III (5%): Spreadsheet Documentation 

You will also have three options for extra-credit:

  • Option I (Group project): Develop an Instrument to measure the impact of BI/BA systems in practice (10% Extra Credit)

OR

The deadline for all lab assignments is seven days after the activity completion in the class unless otherwise stated in the table below:

Course Objectives SLOs* Lab Activity % Deadline
VISUAL ANALYTICS COM, CT, AR  

 

 

Business Dashboard (Tableau)

Online Business Dashboard (Power BI Designer)

Exploratory Visual Analytics (Power BI Designer)

KPI Dashboard (Power BI in Excel)

15% 7 days after completion in class
Report I 5% TBA
DESCRIPTIVE ANALYTICS COM, AR, PS  

 

Web Analytics (Google Analytics)

Sentiment Analysis (Semantria)

10% 7 days after completion in class
PREDICTIVE & DIAGNOSTIC ANALYTICS CT, AR, PS  

 

 

Data Mining: Clustering (RapidMiner / XLMiner)

Data Mining: Classification (RapidMiner / XLMiner)

Data Mining: Decision Tree and Logistic Regression (RapidMiner / XLMiner)

Spreadsheet Modeling (Analytic Solver)

Monte Carlo Simulation (Analytic Solver)

40% 7 days after completion in class
Report II 5% TBA
PRESCRIPTIVE ANALYTICS CT, AR, PS  

 

 

 

Linear Optimization (Analytic Solver)

Linear Programming (Analytic Solver)

Integer Optimization (Analytic Solver)

Decision Analysis (Analytic Solver)

Process Mining (Disco)

20% 05-01
Report II 5% 05-01
BI / BA DEPLOYMENT COM, CT, COL Extra Credit: Group Project 10%** 05-01
ADVANCED ANALYTICS SDL Extra Credit: Try R Programming

Extra Credit: Try SQL Analytics

5%**

5%**

05-01

* Student Learning Objectives: Com: Communication, CT: Critical-thinking, AR: Analytical-reasoning, PS: Problem-solving, COL: Collaboration, SDL: Self-directed learning.
** Extra Credit

GRADE SCALE

Final letter grades will be assigned based on the following scale. You will receive feedback on your progress throughout the semester, but you are always welcome to inquire about your current point total. Your grades will be posted on ITM660 Google Classroom and will be updated weekly.

A+ A A- B+ B B- C+ C C- D+ D D- F
>100 95-100 89-94 85-88 81-84 77-80 73-76 69-72 65-68 61-64 57-60 50-56 <50
adminEvaluation