Management & Data Analytics

Master of Science in Management and Data Analytics (MSMDA)

CIP Code: 52.1301

This program qualifies for the STEM designation.

The goal of the MSMDA program is to prepare analysts who are able to identify and frame business decisions, including acquisition, management, and utilization of big and fast-moving streams of data. Objectives emphasize the creation, analysis, solution, interpretation, and presentation of models using appropriate mathematical approaches and analytical tools by providing an integration of these concepts and skills. The breadth and depth of management and data analytics theories and applications support the ability of graduates to become future industry leaders who can effectively design and manage decision models that can be utilized in the global marketplace.

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Program Objectives

Together, the 12 MSMDA courses provide the knowledge and skills that enable graduates to advance in management and data analyst career fields. Specifically, each group of courses in the MSMDA curriculum measure a student’s ability to:

Apply foundational theories of management and data analytics, which is demonstrated by successful completion of the exercises and projects required in the common- and program-core courses, and capstone course;
Formulate organizational problems to be solved using analytics, which is demonstrated by successful completion of analyses and creation of models required in the program core and elective courses;
Represent data and inform through effective reporting, written and oral communication, and representation of visual analytics, which are required in the program core and electives courses; and
Develop models using both structured and unstructured data from multiple sources, appropriate analytic tools, and ethical considerations, which are required in the program core and electives courses, and capstone course.

Program Length

It is expected that students will take two courses per term throughout their programs. Since many students take one approved quarter-off (vacation term) per year during their program, the normal program length is 2 years (24 months) with the expectation that students will complete in this length of time. Students are given 3 years (36 months) to complete their programs as long as they are making satisfactory academic progress.

Curriculum

Common Core (2 Courses)

Course
Credit Hrs
MGMT515 - Management that Transforms
4.5
TECH515 - Technology that Transforms
4.5

Program Core (5 Courses)

DATA 521 - Tackling Big Data Challenges - Intro to Big Data
4.5
DATA 522 - Solving Big Data Problems – Data Analytics
4.5
DATA 524 - Information Visualization
4.5
INST 522 - Database Design and Processing
4.5
QANT 510 - Statistics for Decision Making
4.5

Elective (4 Courses)

A minimum of 4 elective courses (18 credit hours) are required, which include at least one course from Elective Group 1 and one course from Elective Group 2.

Elective Group 1

DATA 523 - Big Data Technologies
4.5
INST 525 - Business Intelligence and Data Warehousing
4.5
DATA 526 - Advanced Analytics and Modeling
4.5
DATA 530 - Demonstrated Solutions with Analytics
4.5

Elective Group 2

QANT 520 - Probabilistic and Stochastic Models
4.5
QANT 530 - Statistical Estimation and Regression Analysis
4.5
QANT 540 - Deterministic Optimization Models
4.5

Capstone (1 Course)

CAPS600 - Graduate Capstone
4.5