Course Syllabus

Course Description

Part 1: Business Intelligence

This course provides an introduction to business intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Students will learn data mining, visualization, and statistical analysis along with reporting options, such as management dashboards.

 Part 2: Analytics

This course provides an introduction to analytics or the automation of analysis. It also includes an overview of qualitative and quantitative analysis methods and methods used to automate these processes for speed, interactivity, and quality (reliability and validity). Several examples of modern types of analytics such as descriptive, diagnostic, discovery, predictive, and prescriptive approaches will be introduced and explored.

Course Goals

Based on selected focus, students completing this course will understand some of the following concepts and will be able to apply them in various business contexts:

  • Data gathering
    • Source evaluation
    • Data cleansing/interpretation
  • Qualitative analysis
    • Categorize
    • Relationships/Influence
    • Conditional logic
    • Sentiment analysis
  • Data visualization
    • Charts
    • Reports
    • Dashboards
  • Data mining
    • Classification
    • Text mining
    • Web mining
  • Quantitative analytics
    • Description statistics
    • Regression
    • Clustering

Depth of Material Covered

From the readings, students gain familiarity with some of the most common data science techniques used by the industry. The BI/Analytics and Research projects allow students to gain further mastery and knowledge in some of the tools and techniques discussed in the textbook. Students can also look at other tools and techniques related to business intelligence, data analytics, or data science.


Completed one of the following:

  • CIT 111 - Introduction to Databases
  • CIT 160 - Introduction to Programming
  • A course that covers using the Excel data and formula components
  • A course that covers analyzing data


Jordan Goldmeier, Data Smart: Using Data Science to Transform Information into Insight Second Edition.(Wiley, November 2023).

The BYUI Library offers the electronic book free to students.

First, create an account with Safari.
Then, access the book here: Data Smart.

Optional Textbooks to Consider for Further Knowledge

An Introduction to Statistical Learning with Applications in R, by: Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. A free PDF copy of this book is provided by the author on his web page: Introduction to Statistical Learning (select “Download the Second Edition”).

Project-Based Learning

This course is a project-based learning course. Students will complete three projects during the semester.

  1. BI/Analytics project - Students will work as a team to find and solve a specific analytics scenario using the three major patterns of analysis (gathering, patterning, optimizing).
  2. Research project - Students will work individually to research a business intelligence or analytics topic of their choice and share their results.
  3. AI project - Students will work individually or in a team to build an AI that plays a selected game

Project-based learning does not end up at a predetermined outcome or take predetermined paths. During the semester, students will work relatively autonomously to design, solve problems, make decisions, investigate, and create real products. In a project-based learning course, projects are the curriculum—not supplementary activities.

Characteristics of Project-Based Learning

  • Student autonomy
  • Choice
  • Unsupervised work time
  • Student responsibility
  • Authentic problems
  • Complex tasks
  • Real products

Instructor Role in Project-Based Learning

Instructors play a slightly different role in a project-based learning course. Instructors do not direct the learning. Instead, instructors are knowledgeable guides, facilitators, or mentors. The instructor will not organize or lead their projects nor tell students what they must learn, but will help them discover profitable paths, set reasonable scope, and help them find resources, strategies, tools, and information. 


From the BYUI Grading System, “Grades are determined by each instructor based upon an evaluation of all assigned and completed coursework. Classroom/laboratory participation, mastery of subject matter, and promise of continuing success in sequential courses in related fields are all criteria used to evaluate progress.”

Their grade is their responsibility, as well as their instructor's. Use the Canvas Grades to gauge and monitor progress. Please contact the instructor as soon as possible if any errors arise. Students have one week from the date a grade is posted to clarify. The day after the semester ends is too late for corrections.

This course is graded on a point system based on assignments, projects, and participation. 

  • Syllabus Quiz = 7 points
  • Reading Quizzes = 70 points
  • Assignments = 210 points
  • Explore Assignments = 100 points
  • Projects = 300 points
  • Course Evaluation Surveys = 3 points
  • Gospel Integration Discussions* = 60 points

*The instructor may remove all or some gospel integration discussions.

Total Points Available = 735 points.

Late Work Policy

  • All individual assignments and preparation work must be completed before the date and time specified. 
  • Late coursework receives a 10% deduction per day.
  • Two weeks after the due date, coursework is not accepted. Please keep up a good pace with the course.

Academic Dishonesty

Cheating in any form is unacceptable conduct. “For what shall it profit a man, if he shall gain the whole world, and lose his own soul?” (Mark 8:36).  Please make sure that if students use other sources in their work, they clearly attribute the source and make clear what they used in their work. Be clear up front instead of waiting for the instructor to grow suspicious about what sources they used and what they contributed.

CIT 381 Learning Model


Teach One Another


  • Study the textbook, articles, internet, 
    materials, and other provided resources.
  • Complete reading assignments and quizzes.
  • Class discussions.
  • Peer reviews.
  • Team assignment and projects.
  • Assignments.
  • Projects.

University Policies

Students with Disabilities

Brigham Young University-Idaho is committed to providing a working and learning atmosphere that accommodates qualified persons with disabilities. If you have a disability and require accommodations, please contact the Disability Services Office at (208) 496-9210 or visit their website and follow the Steps for Receiving Accommodations. Reasonable academic accommodations are reviewed for all students who have qualified documented disabilities. Services are coordinated with students and instructors by the Disability Services Office.

This course may require synchronous meetings. If you are currently registered with the Disability Services Office and need an interpreter or transcriber for these meetings, please contact the deaf and hard of hearing coordinator at (208) 496-9219.

Other University Policies

Student Honor and Other Policies

Please read through the document called University Policies. It gives important information about the following topics:

  • Student Honor
    • Academic Honesty
    • Student Conduct
      • Sexual Harassment
  • Student with Disabilities
  • Complaints and Grievances
  • Copyright Notice

Go to the Student Resources module to review further resources and information.

Course Summary:

Date Details Due