Applied Data Analytics, Minor

Visit the Information Systems and Technology Department page for more information on the program and access to advising.

Program Description

The Minor in Applied Data Analytics allows students to choose among Information Systems, Statistics, and Marketing courses to learn about data management and analysis.

Program Requirements

Course List

Code	Title	Credit Hours
Total Credit Hours		18
Discipline Core Requirements		6 Credits
INFO 2410	Database Fundamentals	3
INFO 3130	Introduction to Applied Data Analytics	3
Elective Requirements		12 Credits
Complete 12 hours of the following:		12
INFO 3410	Database Systems and Warehousing (3)
INFO 4120	Data Visualization (3)
INFO 4130	Data Science and Big Data Analytics (3)
MKTG 3680	Marketing with Social Media (3)
MKTG 3690	Digital Marketing Analytics (3)
MKTG 4610	Sales Operations (3)
STAT 4100	Design of Experiment (3)
STAT 4200	Survey Sampling (3)
STAT 4400	Multivariate Analysis (3)
STAT 4500	Nonparametric Statistics (3)
BIOL 3100	Introduction to Data Analysis for Biologists (3)
Other advisor-approved elective

Graduation Requirements

1.Completion of a minimum of 18 semester credits.
2.Minimum grade of C- required in all courses.
3.Overall grade point average of 2.0 (C) or above.
4.Residency hours: minimum of 9 credit hours through course attendance at UVU.

Graduation Plan

This graduation plan is a sample plan and is intended to be a guide. Your specific plan may differ based on your Math and English placement and/or transfer credits applied. You are encouraged to meet with an advisor and set up an individualized graduation plan in Wolverine Track.

Plan of Study Grid

First Year
Semester 1		Credit Hours
INFO 2410	Database Fundamentals	3
INFO 3130	Introduction to Applied Data Analytics	3
	Credit Hours	6
Semester 2
Minor Elective		3
	Credit Hours	3
Second Year
Semester 3
Minor Elective		3
	Credit Hours	3
Semester 4
Minor Elective		3
	Credit Hours	3
Third Year
Semester 5
Minor Elective		3
	Credit Hours	3
	Total Credit Hours	18

Program Learning Outcomes

1. Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
2. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
3. Produce computer models, analyses, and visualizations that meet business needs.