Program Description

The Program focuses on theoretical framework, practical applications, and research in the field of business administration in business analytics. Program teaches students to leverage the advanced technical tools of data science to synthesize translate complex and voluminous data into meaningful and productive business intelligence to make informed decisions.

In general, students are expected to complete this program in 24 months or two years. Students who maintain satisfactory academic progress for every three (3) consecutive quarter terms are eligible for a full quarter term break. By the successful completion of this program, students will be conferred the Master of Business Administration in Business Analytics degree in Business Analytics. In addition to the in-class learning of theoretical and practical applications and tools, students must demonstrate their academic achievements through capstone experiences in the forms of internship and thesis.

CALUSA Institute does not offer distance education to students. All courses are taught via traditional classroom format. There are no online courses in the curriculum. All instructions are taught in the English language only.

The Program prepares students for many potential career paths including a variety of executive and management/leadership roles or analytics roles that interpret big data into actionable business strategies to improve operations, finances, and marketing functions by making data-driven strategic decisions (Standard Occupational Classification codes 11-1011.00-11-3131.00, 15-2051.00, 13 1111.00).

Student Learning Outcomes

1. Demonstrate knowledge of management fundamentals such as business acumen, leadership principles, critical thinking, communication skills, practical problem-solving skills, and strategic thinking.
2. Demonstrate knowledge of technical concepts such as data mining and analysis, decision modeling, forecasting and simulation, predictive modeling, and data visualization.
3. Demonstrate how to implement management tools and skills learned.
4. Demonstrate how to deploy technical tools and skills learned.
5. Demonstrate ability to leverage the technical tools to make data-driven strategic business or management decisions in hands-on environment.

Classification of Instruction Program

CIP Code: 30.7102 Title: Business Analytics

MBA BA Course Listing

MBA Course Descriptions

Major Courses

BUS515 Managerial Economics

This is a course designed to teach topics in microeconomics most relevant to key management in making decisions within organizations. Essential maxims covered in this course include demand and supply, costs, strategic interactions, market equilibrium, value creation, profit maximization, and market outcomes. This course will teach how managers use economics as an efficient tool to approach and analyze problems and issues and make efficient economic decisions.

As a core course, the application of the principles taught in Managerial Economics will further facilitate understanding the rest of the MBA curriculum.

BUS520 Financial Management

This course provides an in-depth exploration of financial principles, tools, and strategies essential for effective decision-making in organizations. Students will learn to analyze financial statements, evaluate investment opportunities, assess capital structures, and manage working capital to support long-term organizational goals. Emphasis is placed on applying quantitative and qualitative financial techniques to real-world business and healthcare contexts. Key topics include time value of money, capital budgeting, risk and return analysis, cost of capital, and financial performance evaluation. Through case studies, projects, and simulations, students will develop the ability to interpret complex financial data and recommend sound fiscal strategies that align with organizational objectives and regulatory environments.

MCIS531 Database Design and Implementation

Database Design and Implementation focuses on Database design methodologies (ER and/or UML modeling), database query languages (relational algebra and SQL), database implementation (physical data organization, indexing, query processing and optimization), and database application development (JDBC/ODBC).

MCIS541 Quantitative Methods for Information Systems

Quantitative Methods for Information Systems focuses on mathematical essentials for successful quantitative analysis of problems in the field of information systems as it relates to business analytics. Topics include combinatorial mathematics, functions, and the fundamentals of differentiation and integration. It also includes the study of elementary probability theory, discrete and continuous distributions.

BUS550 Business Analytics

Business Analytics explores the relationships between variables, primarily through multivariate regression. In addition to learning basic regression skills such as modeling and estimation, students will be exposed to hypothesis testing and making inferences and predictions from data. Students will also learn new principles such as identification and robustness. The course has an intense focus on applications relevant to managers, using cases to understand business analytics, interpretations, and decision making.

BUS555 Project Management

Project Management provides practitioners who have current information technology skills with an understanding of the theory and practice of project management through an integrated view of the concepts, skills, tools, and techniques involved in the management of information technology projects in organizations.

BUS560 Applied Business Forecasting

This course equips students with the quantitative and analytical tools necessary to forecast business, economic, and market trends for informed managerial decision-making. Students will explore a variety of forecasting methods, including time series analysis, regression models, exponential smoothing, ARIMA modeling, and qualitative techniques such as Delphi and scenario planning. Emphasis is placed on the practical application of forecasting methods to real-world business, finance, and economic datasets. Students will learn to select appropriate models, validate forecast accuracy, and communicate results effectively to stakeholders. The course integrates statistical software and spreadsheet modeling to support hands-on analysis and interpretation.

MCIS561 Artificial Intelligence and Machine Learning

This course covers advanced topics in Artificial Intelligence (AI) and Machine Learning with focus on how to build and search graph data structures needed to create software agents.

BUS575 Big Data Analytics in Marketing

This course is an introduction to Big Data Analytics and the ways data is used in marketing decisions. The course will focus on the study of how to extract actionable knowledge from a vast quantity of data sets.

MSCIS577 Advanced SQL

The course focuses on design, development, and implementation of SQL programming for all types of relational database applications including client/server and Internet databases. It also covers writing interactive and embedded SQL statements and understanding implications of multi-user database applications.

BUS580 Operations Research

Operations Research focuses on advanced study and research emphasizing topics such as deterministic optimization, probabilistic models and their applications, simulation, and mathematical statistics.

BUS590 Strategic Management

This course integrates knowledge from across the graduate curriculum to develop the skills required for strategic analysis, formulation, and implementation in complex organizational environments. Students will learn to assess external market forces, internal resources, and competitive positioning to craft strategies that achieve sustainable competitive advantage. Topics include environmental scanning, SWOT and value chain analysis, corporate governance, competitive and cooperative strategies, innovation management, and strategic leadership. Emphasis is placed on evidence-based decision-making, scenario planning, and aligning strategy with organizational mission, culture, and stakeholder expectations. Case studies, simulations, and applied projects will challenge students to address dynamic business conditions and create actionable strategic plans.

Internship

BUS605 Internship in Business Management and Analytics

The internship course is a required, credit-bearing academic experience designed to integrate classroom learning with supervised professional practice directly related to the student’s field of study. Students engage in structured, progressively responsible work that allows them to observe, apply, and evaluate disciplinary theories, methodologies, and professional standards in a real-world setting. The internship culminates in a thesis-level analytical paper in which the student critically assesses the organization’s practices and produces a formal, evidence-based recommendation for the company. Completion of this academic work requires sustained engagement with organizational processes professional workflows, and project development over time.

The internship may be completed over a period ranging from a minimum of one academic quarter to a maximum of four academic quarters to support appropriate experiential learning and academic depth. A minimum duration of one quarter (approximately three months) allows adequate time for orientation, substantive participation, observation, and reflective analysis aligned with course learning objectives, while a longer duration enables participation in extended projects and increased professional responsibility. Throughout the internship process, the student works closely with a faculty advisor to engage in guided discussion and complete assigned academic tasks that connect internship experiences to curricular learning outcomes.

Thesis

BUS610 Thesis in Business Management and Analytics

Students integrate advanced academic study with supervised professional practice directly related to the Business Management and Analytics program. Under close faculty guidance, they conduct in-depth research and critical analysis to examine an organization’s practices, methodologies, and professional standards through the lens of disciplinary theory and evidence-based frameworks. The work results in a comprehensive, thesis-level paper that evaluates organizational operations and presents well-supported, actionable recommendations. Limited part-time professional engagement may occur to support consultation, data gathering, and applied analysis, while maintaining academic inquiry and scholarly research as the primary focus.

Students are required to have successfully completed at least twenty-eight (28) course credits in the Business Administration in Business Analytics program prior to registering this course. Students are responsible for arranging the availability of the thesis advisor and principal reader. The thesis advisor must be a full-time faculty member.

Graduation Requirements

To be conferred the Master of Business Administration degree in Business Analytics degree, a total of at least 56 quarter credits in the Program Curriculum must be completed by the student with a minimum Cumulative Grade Point Average (CGPA) of 3.0.

Candidates for graduation must obtain an Application for Graduation Form from the Administration Office and submit it to the Registrar. Students are advised to file the application during the term preceding the one in which
they expect to graduate.

During each course registration period, candidates meet with their academic advisors to determine if their proposed course schedule meets the graduation requirements.

All tuition and school fee account balances must be paid in full sixty (60) days prior to graduation. Student’s payment of the graduation fee is mandatory regardless of his or her attendance in the graduation ceremonies.