A degree in Applied Data Analytics provides the expertise to convert raw data into actionable insight for decision making. A data analyst can use data to determine what happened, why it happened, what will happen, and what should be done. Using modern tools and methods, a data analyst is able to create meaning from data. In addition to creating new actionable knowledge, the data analyst is also skilled in sharing the findings with others using visualizations and clear communications. In this applied program, students learn more than the theoretical analysis methods; they learn how to solve real-world problems. The curriculum includes the use of the R and SQL languages to prepare and analyze data, Python to conduct more complex analysis methods, and Tableau to apply higher-level tools for analysis and producing effective visualizations. Throughout the curriculum, students have opportunities to select their own data and choose problems they wish to study so that they can apply their unique expertise to study relevant data and generate meaningful insights. The curriculum concludes with a capstone project where students design and conduct their own data analytics research study.
Contact Information
Learning Outcomes
The student completing the Masters Degree in Applied Data Analytics 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.
Requirements
Students must achieve the following program requirements for all courses listed under Program Requirements and Program Required Courses for the Applied Data Analytics, M.S.
Program Requirements
Major Credits: 37
Minimum GPA: 3.0
Minimum Grade: C
Foundational/Prerequisite Course Requirement: Inferential Statistics
Program Required Courses
| Code | Title | Credits |
|---|---|---|
| CIS 6105 | Data Analytics for Decision Making | 3 |
| CIS 6107 | Data Storage and Retrieval | 3 |
| CIS 6110 | Applications of Data Analytics | 3 |
| CIS 6113 | Legal and Ethical Considerations of Information Technologies | 3 |
| CIS 6115 | Applications in Machine Learning | 3 |
| CIS 6117 | Applied Text Analytics | 3 |
| CIS 6118 | Big Data Management | 3 |
| CIS 6204 | Data Visualization and Storytelling | 3 |
| CIS 6208 | IT Project Management | 3 |
| CIS 6209 | Adopting a Data Analytics Practice | 3 |
| CIS 6700 | Experimental Design Data Analytics | 3 |
| CIS 6780 | Data Analytics Project I | 2 |
| CIS 6790 | Data Analytics Project II | 2 |
| Total Credits | 37 | |
Degree Requirements
To graduate from The College of St. Scholastica, graduate students must meet the following minimum degree requirements.
Minimum GPA: 3.0