Master of Science in Applied Data Analytics

Master of Science in Applied Data Analytics

Philosophy 
Over the past several decades, organizations have used information systems to automate business processes. Through both integrated and isolated systems, organizations have collected and continue to collect large volumes of data. Many organizations have discovered the value of this data leading to new and improved products and services, improved process efficiencies, and better decision making. Transforming all of this disparate data into meaningful insight requires specialized skills and techniques in data science.

The Master of Science in Applied Data Analytics degree is designed to enable students to apply modern technologies and methods to create meaningful and actionable insight to support problem-solving and decision making. Students develop the skills and knowledge needed to successfully execute and lead data analytics practices. Throughout the courses, students are introduced to skills, techniques, and methods to identify, transform, and analyze data and communicate the new insights.

Program Description
The Master of Science in Applied Data Analytics program prepares students for a career in the data science field. The Applied Data Analytics program develops students proficient in the concepts, skills, and techniques of applied data science. Additionally, this degree program prepares students to lead organizational efforts to develop and adopt ethical data analytics practices.

Format
The 37 semester credit program is offered through an online format, which allows professionals to maintain their current employment status while enhancing their knowledge and skills. Students enroll in the foundational and advanced courses during the first year and specialization courses and capstone project during the second year. All courses are taken online and the program ends with a student research symposium on the Duluth campus.

Program Outcomes
Upon completion of the Project Management program at The College of St. Scholastica, the graduate will be able to:

  • Evaluate business challenges and formulate questions leading to solutions
  • Identify data needs to answer business questions
  • Apply modern techniques to retrieve and prepare data for analysis
  • Select and apply proper tools and analytical models
  • Communicate results as action-oriented and meaningful
  • Integrate ethical considerations in data collection and reporting

Admission Requirements

The Master of Science in Applied Data Analytics program considers applicants who:

  1. Submit a completed Graduate Admissions Application form online.
  2.  Earned a baccalaureate degree from an accredited college or university.
  3.  Completed an undergraduate statistics course with a grade of C or better
  4.  Have a minimum two years of experience working with data.
  5. Submit all official transcripts of relevant course work necessary for admission.
  6. Earned a minimum cumulative GPA of 2.8 in undergraduate coursework.
  7. Submit a completed Master of Science in Applied Data Analytics Essay.
  8. Submit two Graduate Recommendation forms from individuals who have observed or evaluated your leadership competencies or abilities.

International Applicants will need to complete additional admission requirements.
Note: Meeting minimal entrance requirements does not necessarily guarantee admission.

Application Deadline
Application deadlines for priority consideration:

  • Deadline is August 15 for the Fall start
  • Deadline is January 1 for the Spring start

Review of completed application files will continue until all open seats for the program are filled.

Degree Requirements
A total of 37-semester credits are required for graduation, including credits for the capstone project. Credit toward the degree will be given for courses with a grade of 2.0 or better; students are expected to maintain a minimum cumulative grade point average of 3.0. A maximum of six (6) graduate semester credits may be transferred from another college or university if approved by the student's advisor and/or the program director. The Master of Science in Applied Data Analytics graduate program must be completed within seven years and students must make sufficient academic progress toward the degree during their enrollment. Students not enrolled for more than two consecutive semesters are required to reapply to the program before enrolling in additional courses. Credits that are more than seven years old as of the date of graduation do not count toward the degree.

Curriculum
The Master of Science in Applied Data Analytics curriculum is made up of 13 courses for a total of 37 credits. The curriculum consists of 4 foundational courses to prepare students with the basic data analytics skills and knowledge, 3 advanced data analytics courses, 3 enterprise analytics specialization courses, and 3 courses associated with the capstone project. The foundational courses should be completed prior to enrolling in the advanced and specialization courses and the course prerequisites are identified in the course descriptions.Summary of Curriculum

Foundational Courses
CIS 6105: Data Analytics for Decision Making
CIS 6107: Data Storage and Retrieval
CIS 6108: Advanced Data Analytics
CIS 6113: IT Management Ethics

Advanced Courses
CIS 6115: Applications in Machine Learning
CIS 6117: Applied Text Mining
CIS 6118: Big Data Management

Specialization Courses
CIS 6553: Enterprise Data Strategies
CIS 6557: Enterprise Data Architectures
CIS 6558: Changement Management for Data Analytics

Capstone Project Courses
CIS 6795: Research and Writing
CIS 6800: Capstone Project I
CIS 6900: Capstone Project II