Master of Science in Data Analytics (MSDA)

Program Description

The Master of Science in Data Analytics (MSDA) program provides learners with the skills to leverage data to drive business strategy and value. The program combines data mining, programmatic data analysis, statistical modeling, and data visualization courses with a solid foundation of soft skills and business education to transform learners into data-driven decision-makers and leaders.

Nexford University selected the Master of Science in Data Analytics (MSDA) degree for two primary reasons:

1. MSDA aligns with the University's primary focus on programs that merge business and technology.

2. MSDA provides both technical and business skills that are in high demand across all industry sectors.

Program Outcomes

1. Select appropriate data analytics tools to collect and analyze data.

2. Design and implement a data repository for architecting data integration solutions.

3. Create and maintain predictive models using machine learning to address future business needs.

4. Formulate conclusions derived from data to make data-driven decisions.

5. Communicate and present data insights and information visually and verbally.

6. Distinguish modern social, legal, and ethical issues arising from the use of emerging technologies.

7. Apply critical thinking skills through the interpretation of the data analysis process.

8. Assess personal and professional resources and learning opportunities for staying current in industry best practices.

BAN 6800 Data Analytics Capstone Course Outcomes

1. Explain the importance of making data-driven decisions in the context of modern businesses and how it impacts various aspects of a company, such as marketing, revenue, operations, and hiring.

2. Apply the concepts of business analytics to a real-world business challenge, using appropriate data analysis techniques and tools to address the issue.

3. Examine the data collected during the Business Analytics Capstone Project and identify patterns, trends, and relationships between different variables.

4. Investigate the interaction between financial and non-financial indicators and their impact on the overall business performance.

5. Develop a comprehensive plan of action for optimizing data usage in a company, integrating the insights gained from the analysis and addressing the identified business challenge.

6. Assess the effectiveness of the data analytics plan in addressing the business challenges and progress towards desired outcomes.

7. Research organizations and resources that are crucial in the advancement of business analytics and leverage this information both within the class and in the workplace.

Program Structure

* Denotes courses that have prerequisite(s). Refer to the course descriptions for further details.