BS in Business Management with Specialization in Business Analytics

BAFBANA

Fundamentals of Business Analytics

This undergraduate course introduces students to the foundational concepts and techniques of business analytics, emphasizing the power and importance of data visualization. In the modern digital age, businesses and organizations are inundated with vast amounts of data. The ability to visually represent this data in a meaningful and insightful manner is crucial for informed decision-making. This course aims to equip students with the knowledge and tools necessary to create compelling visual representations of data, allowing for clearer understanding and communication of complex information. By the end of the course, students will have a comprehensive understanding of the role of data visualization within business analytics and will be adept at using visualization tools and techniques to convey data- driven insights effectively.

BAFWARE

Fundamentals of Data Warehousing

This course introduces how information system are utilized as a decision support system. This course will help the students make sense of the data by applying the knowledge in data warehousing and business intelligence. As an introduction, the students will be given a refresher to some practical office applications of Excel. The students will then be introduced to the concept of database technology and database design using MS Access where theories in relation to normalization, entity-relationship-diagram (ERD) will be covered. Concepts on queries and reports will also be introduced. On the other hand, Power BI will be used to better appreciate data warehousing and business intelligence for data visualization.

BAFDESC

Fundamentals of Descriptive Analytics

This course introduces students to the science of business analytics. The goal is to provide students with the foundation needed to apply data analytics to real-world challenges. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making. The course also aims to provide tools for processing raw data into formats that can facilitate drawing of summarizing statistics. Visualization techniques complemented and or generated from spreadsheet data processing shall be discussed to help in data interpretation. Statistical tools and techniques presented in the course shall guide students on how to properly interpret results of data analysis.

BAFPRED

Fundamentals of Predictive Analytics

This undergraduate course introduces students to the foundational concepts and techniques of predictive analytics, with a primary focus on regression analysis. As businesses and organizations increasingly rely on data to make informed decisions, the ability to predict future outcomes based on historical data has become a vital skill. This course aims to equip students with the knowledge and tools necessary to develop, validate, and interpret regression models for predictive purposes.

BAFPRES

Fundamentals of Prescriptive Analytics

This is a three-unit course which provides business students with the necessary skills in decision making anchored on the science of quantification. This covers the judicious use of business information from the internal and external loci of the organization as bases in making business decisions. Emphasis is made on that business analytics is not a theoretical discipline: these techniques are only interesting and important to the extent that they can be used to provide real insights and improve the speed, reliability, and quality of decisions. The concepts learned in this class should help students identify opportunities in which business analytics can be used to improve performance and support important decisions. It should make them alert to the ways that analytics can be used, or misused, within an organization.

BAINTER1

Fundamentals of Business Analytics

This course is a client-engaged practicum that requires students in the Business Analytics specialization to complete a minimum of 300 hours of supervised professional engagement through on-the-job training (OJT) with organizations engaged in business analytics or data-driven decision-making. Students, working individually or in teams, are assigned to specific, time-bound analytics projects and function as project consultants under the supervision of a designated company mentor or manager. The practicum enables students to apply business analytics concepts, tools, and technologies in real organizational contexts, generate data-driven insights to support managerial decision-making, and communicate findings effectively to stakeholders. It also aims to develop professional competence, ethical responsibility, and reflective understanding of organizational practices, management styles, and the strategic role of analytics in achieving business objectives.

BAINTER2

Analytics Internship 2

Students specializing in Business Analytics are required to complete a 300-hour practicum through on-the-job training (OJT) with local companies engaged in data science and business analytics. The practicum may be undertaken as a one-month full-time summer engagement or an equivalent schedule totaling 300 hours. Students are responsible for identifying host organizations willing to accept them as trainees, and the tasks assigned must be directly related to business analytics. The practicum aims to provide students with authentic workplace experience, exposure to diverse management styles and organizational procedures, and opportunities to apply their academic learning to real-world business analytics contexts.

THSBUS1

Thesis 1

Thesis 1 focuses on the development of a research proposal that demonstrates the student’s ability to integrate and apply knowledge and skills acquired across the Business Analytics curriculum. Students are required to identify a relevant organizational or industry problem and design an analytics-driven research study grounded in big data, quantitative analysis, and evidence-based management. The course emphasizes problem formulation, literature review, research design, data sourcing, analytics methodology, and ethical considerations. By the end of the course, students are expected to produce a defensible thesis proposal that clearly articulates how business analytics tools and techniques will be used to generate actionable insights.

THSBUS2

Thesis 2

Thesis 2 focuses on the execution, analysis, and interpretation of the approved thesis proposal developed in Thesis 1. Students implement their research design by collecting, processing, and analyzing data using appropriate business analytics, statistical, and big data techniques, and present results that address the stated research objectives. The course emphasizes rigorous data analysis, results presentation, discussion of findings, managerial implications, and conclusions grounded in analytics-driven evidence. Students are expected to demonstrate analytical rigor, critical thinking, and professional communication through a completed thesis that contributes practical and theoretical insights relevant to business and management contexts.