Applied Business AnalyticsBack to Course Guide
This course is the introductory course for the Master of Science in Enterprise Analytics. Students will become familiar with an overview and framework for understanding business analytics principles. Students will also be introduced to the theories, strategies, tools, and applied statistical techniques necessary to master the implementation of enterprise analytics to gain a competitive advantage. The course will focus on applying predictive analytics methods, processes, and best practices to common problems faced by organizations. Students will acquire knowledge of the tools, techniques, and processes needed to effectively employ enterprise analytics applications such as statistical modeling, machine learning, artificial intelligence, linear/non-linear programming, optimization, and root cause analysis.
UPON COMPLETION OF THE COURSE, THE STUDENT WILL BE COMPETENT IN:
- Identifying and evaluating influential literature relevant to Business Analytics topics.
- Synthesizing and applying universal ethical principles to Business Analytics in modern organizations.
- Identifying, evaluating, and applying Business Analytics principles and techniques within the context of the modern organization.
- Understanding the implications of producing valuable insights for decision-making based on in-depth analyses of large amounts of internal and external data.
- Discussing the importance of engaging current and future stakeholders through building an organizational environment that balances decision support needs and expectations against the validity of the data sources available.
- Managing the challenges associated with data science personnel and resources.
- Analyzing, evaluating, and applying stakeholders’ feedback to prioritize and improve future Business Analytics applications.
- Analyzing, evaluating, and applying Business Analytics best practices for effective coordination and informed decision-making in modern organizations.
- Creating and cultivating an environment of transparency, trust, conflict resolution, and high performance in the application of Business Analytics.
- Producing and maintaining an evolving Business Analytics plan, from initiation to closure, based on organizational goals, values, risks, constraints, stakeholder feedback, and review of findings.
- Discussing the importance of evidenced-based learning (inspection and adaptation) in Business Analytics applications.
- Integrating continuous quality improvement, effectiveness, the value of the product, process, and team concepts into Business Analytics.