Faculty:

• Gregory Barry, M.S.

• Jared Burns, Ph.D.

• Priyan Kumar, Ph.D.

Learning Objectives: Data Analytics

1. Proficiency in Business-Centered Programming and Algorithms: Develop proficiency in programming languages and apply algorithms and data structures to solve business problems efficiently.

2. Database Management for Business Insights: Design, manage, and query relational and non-relational databases to support business operations, reporting, and strategic decision-making.

3. Applied Machine Learning and Data Science in Business Contexts: Implement machine learning techniques and advanced data science methods to address real-world business challenges and uncover actionable insights.

4. Mathematical Modeling for Business Solutions: Utilize principles of calculus and linear algebra to develop and analyze mathematical models that drive business decisions.

5. Discrete Mathematics and Graph Theory for Operational Efficiency: Apply discrete mathematics and graph theory in areas such as supply chain optimization, financial modeling, and logistics.

6. Probability and Statistical Methods in Business Analytics: Use advanced statistical methods and probability theory to interpret business data and forecast market trends.

7. Foundational Data Science for Business Projects: Understand the principles of data science and apply them to business scenarios, from customer segmentation to product recommendations.

8. Big Data Technologies for Business Intelligence: Leverage big data technologies to analyze large datasets and generate insights that enhance competitive advantage and drive business growth.

9. Time Series Analysis for Business Forecasting: Develop forecasting models based on time series analysis to guide business planning, budgeting, and inventory management.

10. Effective Communication of Business Analytics: Translate data insights into clear and persuasive narratives to inform stakeholders and support strategic decision-making.
11. Simulation and Modeling of Business Processes: Apply modeling and simulation techniques to optimize business operations and assess the impact of potential strategies.

All candidates for the Bachelor of Science degree in data analytics must complete the Liberal Arts Curriculum requirements, the capstone assessment requirement (SDS 300), and the required major courses.

A minimum of 120 credits is required.