Master in Applied Business Analytics

Master in Applied Business Analytics (MABA) is UA&P’s pioneering program that was launched in 2018. It is a 2-year part-time graduate program for experienced professionals in any industry who want to seize the power of data and analytics in his/her work for his/her organization. MABA will enable its graduates to reconnect to the world’s new social landscape intricately painted by the pandemic. With the analytics expertise, they will collaborate with their colleagues in charting a path to the next normal that unfolds new horizons and opportunities for everyone. They will help enable governments, businesses, and individuals to creatively define the right analytics solution for their citizens, employees, customers, and selves as they treat data with ethics and values.

Graduate Outcomes

UA&P MABA graduates will have the capacity to carry out the following:

  1. Help institutions/companies use analytics as strategic tool for decision making.
  2. Describe and visualize data and communicate its insights effectively in story form.
  3. Correctly apply analytics processes, techniques, algorithms and tools on actual data to derive insights to solve business problem/s.
  4. Design and implement data management processes from acquisition or creation, storage, retrieval and maintenance of data that will be analyzed.
  5. Plan, manage, evaluate and direct analytics projects from beginning to end.
  6. Follow the research process in completing an analytics project.
  7. Identify, define, and resolve ethical and legal concerns specific to data analytics as they pertain to persons, organizations, and society.

Program Delivery

The key to a successful analytics program for business students is in the implementation. As an applied business analytics program, MABA is an applied, multi-disciplinary, experience building, and collaborative program. Its pedagogy and emphasis will differ from Data Science programs. Faculty from the academe and industry work together to combine theory and practice i.e., integrating business, technology, communication, and quantitative disciplines with liberal education.  Our partnership with the Analytics Association of the Philippines (AAP) and sponsor-companies will help you work on real problems of real clients with actual data for your analytics course projects. Courses are project-oriented employing inquiry-based approach to learning to build thinking skills such as critical thinking and problem-solving skills.

Curriculum

Foundational Courses

  • Business and Management Theories, Concepts, and Cases  (2 units)
    This course provides the students with an opportunity to demonstrate understanding of the underlying theories, concepts, and principles in organization, business, and management domains including the critical analysis of various internal and external factors affecting them. It aims to help the students explore and make sense of  contemporary issues, cases,  trends and constructs in managing  today’s business organization, especially those that pertain to key business functions such as  marketing, strategy,  finance, accounting, human resources, information systems, and operations. The students will also be guided on how to critically examine and analyze business decisions in each of afore-mentioned business functions.

  • Mathematics for Analytics (2 units)
    The course will focus on math topics that are necessary in understanding concepts in analytics. It includes topics in linear algebra, specifically matrices and their applications. This course will also cover basic concepts in differential and integral calculus and their applications.

  • Computing for Analytics (2 units)
    This course aims to equip MABA students to perform basic computing for data analytics. The course will introduce and discuss the use of Python, a high level programming language that is among the most popular languages for performing analytics at present.The course will use Anaconda, a popular package for doing projects in analytics. Anaconda includes Jupyter Notebooks, a tool that runs on a web browser and can execute codes in Python and R, among other programming languages. Jupyter combines both code and text formatting, thus facilitating not only the meaningful presentation of an analytics project, but also its reproducibility.

    Topics in the course include fundamental Python programming concepts, use of Python modules in general, and discussions on specific Python modules commonly used in performing data analytics: numpy for scientific computing, pandas for data manipulation, and matplotlib for plotting.

  • Business Strategy and Analytics (2 units)
    The course will focus on the use of data as a strategic tool for decision making. It will instill a general analytical intuition needed to develop strategies for organizations to compete and operate more effectively and efficiently. Students will understand the organizational environment in which Analytics exists. They will learn the interaction of many competencies, people, and processes involved in any Analytics project to properly manage the information flow between the business-driven and technically-oriented environments.

  • Data-Driven Organization and Management (2 units)
    This course will teach the students the relevance, challenges and value of building a data-driven enterprise where the role of data and analytics are integral to business decision-making. The students will (1) learn the fundamentals of building a data-driven organization; (2) assess and unlock the business opportunities and create value moments; (3) discern the importance of leadership and influencing skills; (4) design an applicable data-driven ecosystem anchored on business goals.

  • Descriptive Analytics, Visualization, and Storytelling (Storifying Analytics) (2 units)
    This course is officially called Descriptive Analytics, Visualization, and Storytelling. But to simplify, we’re calling it Storytelling with Data to highlight the main thrust of this course — to teach one how to tell an engaging and effective story with the data and analysis at hand. In this class, we preach “STORY FIRST” to emphasize that no amount of analytics is useful if it cannot be communicated and understood. In this 2-unit course, we shall focus on three skills, which will serve as the modules: (1) Transforming your data and insight into a compelling story, (2) Representing your story with effective visuals and data visualization, and (3) Delivering your story orally in the simplest and affective manner possible.

  • Statistical Computing (2 units)
    This course will introduce the basics foundation of Statistics. It will take students to undergo the process of data analysis which is very crucial in the data science practice; from getting to know the data, spotting anomalies and dealing with them, exploring patterns, formulating hypothesis, and testing them then finally making inferences based on findings. Moreover, with the growing use of technology today, this course will be taught manually and with the use of R. The students are expected to have at least a background on basic mathematical notation and some algebra. Knowledge of basic Statistics and R will be beneficial.

  • Insight Development and Innovation (2 units)
    In this course, the student will learn how to develop and leverage consumer insights to inspire brand and business growth. The student will be able to:  (1) acquire a deeper understanding of consumer psyche and behavior; (2) develop and leverage consumer understanding to generate insights through the step-by-step insight generation process; and  (3) identify the innovation approach that will bring to life the most relevant insight that will respond to a business opportunity.

  • Analytics Algorithms 1 (2 units)
    The course will cover popular data mining frameworks to model patterns and trends in the data to understand the future or fill in missing information. It will introduce computational methods in statistics, natural language processing and machine learning, and how these techniques are integrated and deployed to effectively harness the power of predictive analytics in an organization. Model implications, impact, and assumptions will be discussed as they pertain to a variety of business problems. Students will learn common supervised and unsupervised methods, algorithms and techniques for answering predictive questions from data.

  • Human Perspective of Analytics (2 units)
    This ethics course is fundamentally grounded on a philosophical anthropological understanding of the human person. It builds on the premise that the human person starts at the moment of conception and is essentially structured with a nature that comprises of a body, emotions, and a spiritual soul, all of which have their dynamic natural tendencies towards their ends. A clear understanding of these tendencies, the basic features of the person, and especially the will and freedom are key to an ethics that is suited to the flourishing of the person as a human being. The course offers principles not merely to avoid doing what is evil as required by human dignity but aims at promoting the excellence that is worthy of being human (Greek arete, Eng. virtues). Ethics proper specifically studies the nature and principles of human action but the perspective adopted is how human action aligns with the last end of the person. This means that it takes on the natural law framework in the critical assessment and evaluation of ethical issues.  It includes virtues because it is not possible to be a good person without the perfection of the human powers that enable us to do the good.

  • Management of Analytics Projects (2 units)
    The course will cover the fundamentals and standards of project management as outlined by the Project Management Institute in the Project Management Body of Knowledge (PMBOK®). However, Analytics projects are often characterized by uncertain or changing requirements and high implementation risk. The course will, therefore, cover as well various project methodologies – such as the Waterfall Model and Agile – and various Analytics methodologies – such as the Kimball Lifecycle Methodology, KDD, SEMMA, and CRISP-DM – to determine the most apt project management approach to successfully deliver Analytics projects from beginning to end.

  • Programming for Databases (2 units)
    This course is about database systems and how to programmatically interact with them. It includes representing information with the relational database model, manipulating data with an interactive query language (SQL) and database programming. The course will also touch on designing, implementing and querying data warehouses in a relational database. Finally, students will be introduced to NoSQL databases that are also widely used to enable analytics and processes and tools used to ensure data integrity and security

  • Analytics Algorithms 2 (2 units)
    The course will cover theories and practices aimed at identifying solutions to an optimization problem given the constraints and the objective. It will start where the predictive analytics course left off, covering more advanced topics: time series forecasting, support vector machines, deep learning, and natural language processing. Additionally, it will introduce computational methods in operations research e.g. optimization and simulation models, linear programming, and transportation problem. Students will be able to transform a given optimization problem into analytical models to provide decision-makers with advice on what best action to take.

  • Data Engineering (2 units)
    This course deals with the processes and techniques used to move data from different formats and from different sources into something that can be readily and efficiently used for analytics. Using what they learned from the Basic Computing and Programming for Databases projects, students will learn to perform Extract, Transform and Load (ETL) data from different types of sources to a data warehouse. The latter part of the course will also discuss cloud computing and tools typically used in the industry to achieve moving large amounts of data in an efficient and timely manner.

  • Ethics and Law in Data Analytics (2 units)
    The course will cover the ethical and legal frameworks of data analytics. Powerful tools in analytics to create real-world outcomes which are either for good or for ill. Students will develop and implement data management governance and strategies that incorporate privacy and data security, policies and regulations, and ethical considerations.

  • Capstone | 6 units (Broken in two courses i.e., Capstone 1 and 2)
    The capstone research project is a culminating course where a student applies the science of analytics to data to inform strategic and operational decisions that will drive business and organizational value with humanist, ethical and legal perspectives and presents the analytics solution to a panel. While under the guidance of a Capstone adviser and/or industry expert and business domain advisers, the project is an independent individual analytics research project.

Faculty and Capstone Advisers

MABA students will be mentored by the following esteemed faculty and capstone advisers:

Armin Paul D. Allado
Division Chief – Risk Management Division, Bureau of the Treasury
Master of Science in Analytics, Georgia Institute of Technology
Master of Science in Finance, London School of Economics
Master of Science in Applied Mathematics, University of the Philippines – Diliman
Bachelor of Science in Management Engineering, Minor in Financial Management, Ateneo de Manila University

Engr. Gregory Michael A. Berces
PhD in Business (units earned), De La Salle University
Master in Business Administration, Ateneo de Manila University
Bachelor of Science in Electronics and Communications Engineering, Mapua Institute of Technology

Antonio C. Briza
Consultant, University Center Foundation
Master of Science in Computer Science, University of the Philippines – Diliman
Bachelor of Science in Computer Science, University of the Philippines – Diliman

Reynaldo C. Bonita, Jr.
Lecturer, University of Asia and the Pacific
Master of Data Science, Monash University, Australia
Bachelor of Science in Information Technology, University of Asia and the Pacific

Cyrus Paolo M. Buenafe
Department Chair, Department of Information Science and Technology
Program Director, Master in Information Technology (MIT)
Program Director, Bachelor of Science in Information Technology (BSIT)
Master of Science in Information Technology, University of Asia and the Pacific
Master of Arts in Economics, Ateneo de Manila University
Bachelor of Science in Information Technology, University of Asia and the Pacific

Atty. Jo Aurea M. Imbong
University Counsel, University of Asia and the Pacific
Faculty, University of Asia and the Pacific
Faculty, Ateneo de Manila University
Bachelor of Law, University of the Philippines – Diliman

Yves Y. Kangleon
Director – Customer Analytics and Loyalty, Cebu Pacific Air
Master in Business Administration, De La Salle University
Bachelor of Science in Mathematics, Ateneo de Manila University

Raymond Freth A. Lagria
Assistant Professor, Department of Industrial Engineering and Operations Research, University of the Philippines – Diliman
Subject Matter Expert, Project SPARTA
Mentor, Business Analytics Program for IT-based Organizations
Master of Science in Industrial Engineering, University of the Philippines – Diliman
Bachelor of Science in Industrial Engineering, University of the Philippines – Diliman

Macrina P. Lazo
Head of Banking Analytics, Eastwest Bank
Master in Business Economics, University of Asia and the Pacific
Bachelor of Science in Statistics, University of the Philippines – Diliman

Ruth L. Legaspi
Assistant Vice President for Business Development Strategic Planning and Analytics, McDonald’s Philippines
Bachelor of Arts in Communication major in Communication Research, University of the Philippines – Diliman

Alexander Ken P. Libranza
Manager, Restaurant Systems Department, Chowking Fresh & Famous Foods, Inc. (Jollibee Foods Corporation)
Lecturer, University of Asia and the Pacific
Lecturer, University of Santo Tomas
Master in Applied Business Analytics, University of Asia and the Pacific
Bachelor of Science in Agribusiness Economics, University of the Philippines – Mindanao

Dominic Vincent D. Ligot
Founder & CTO, CirroLytix Research Services
Co-founder, Analytics Association of the Philippines (AAP)
Board of Trustees, Philippine Center for Investigative Journalism (PCIJ)
Founder & Director, Data Ethics PH
Senior Data Scientist, UNDP
Postgraduate, Clinical Epidemiology, Utrecht University
Postgraduate, Data-driven Marketing, Advanced Marketing Research, Cornell University – Johnson Graduate School of Management
Bachelor of Science in Business Administration, University of the Philippines – Diliman

Ruel V. Maningas
Program Director, Master in Applied Business Analytics (MABA)
Adjunct Assistant Professor, University of Asia and the Pacific
PhD major in Extension Education and minor in Computer Science, University of the Philippines – Los Baños
Master in Management (M.M.) major in Development Management, University of the Philippines – Los Baños
Bachelor of Arts major in Economics, Colegio de San Juan de Letran – Calamba

Dean Edward A. Mejos
Instructor, University of Asia and the Pacific
Master of Arts in Philosophy, University of Santo Tomas
Bachelor of Arts in Philosophy, University of Santo Tomas

Jodie Claire A. Ngo
Program Director, Bachelor of Science in Business Administration (BSBA)
Operations Committee Secretary, School of Management (SMN)
Ph.D. in Business (candidate), De La Salle University
Master of Science in Management, University of Asia and the Pacific 

Elmer C. Peramo
Senior Science Research Specialist, Advanced Science and Technology Institute (ASTI-DOST)
Master of Engineering in Electrical Engineering, University of the Philippines – Diliman
Bachelor of Science in Computer Science, Mondriaan Aura College

Sherwin M. Pelayo
Chief Analytics Officer at Eclaro
Co-Founder, Analytics Association of the Philippines (AAP)
Bachelor of Science in Physics, Ateneo de Manila University

Maria Veronica P. Quilinguin
Assistant Professor, University of Asia and the Pacific
Ph.D. in Mathematics, University of the Philippines – Diliman
Master of Science in Mathematics, University of the Philippines – Diliman
Bachelor of Science in Applied Mathematics, University of the Philippines – Diliman

Brenda A. Quismorio
Business Process and Analytics Lead, Corporate Planning and Review, UA&P
Co-founder, Analytics Association of the Philippines
Ph.D. in Business Administration, University of the Philippines – Diliman
Master of Science in Management, University of the Philippines – Diliman
Master in Business Administration, University of the Philippines – Diliman
Bachelor of Science in Statistics, University of the Philippines – Diliman

Fatima R. Ravalo
Lecturer, University of Asia and the Pacific
Market Research Consultant
Bachelor of Science in Statistics, University of the Philippines – Diliman

Rafael April S. Rivera
Deputy Team Leader (Transport, Supply Chain, and Logistics), USAID UPPAF RESPOND Project
Board Member (Treasurer), Planning and Development Research Foundation, Inc. (PLANADES)
Member, DTI CMCI Technical Working Group
Lecturer, University of Asia and the Pacific
Lecturer, Development Academy of the Philippines
Lecturer, De La Salle – College of Saint Benilde
Registered Environmental Planner (EnP)
Ph.D. in Urban and Regional Planning Major in Transport Planning (candidate), UP School of Urban and Regional Planning
Master of Science in Industrial Economics, University of Asia and the Pacific
Bachelor of Arts in Humanities, University of Asia and the Pacific

Eva M. Rodriguez
Assistant Professor, University of Asia and the Pacific
Ph.D. in Mathematics, University of the Philippines – Diliman
Master of Science in Mathematics, University of the Philippines – Diliman
Master of Arts in Education Major in Liberal Education, University of Asia and the Pacific
Bachelor of Science in Mathematics, University of the Philippines – Diliman

Lota Kristine C. San Juan-Nable
Program Director, Master of Science in Management (MScM)
Manager, Business-Academe Partnership (BAP) Program
Consultant, Department of Trade and Industry (DTI)
Ph.D. in Business (candidate), De La Salle University
Master of Science in Management, University of Asia and the Pacific

Millicent H. Singson
Senior Data Scientist, Manulife
Co-founder, 5Fold Solutions
Master of Science in Data Science, Asian Institute of Management
Bachelor of Science in Applied Physics, University of the Philippines – Diliman

Varsolo C. Sunio
Specialist, Accenture
Ph.D. Urban Management, Kyoto University, Japan
Master of Science in Industrial and Systems Engineering, National University of Singapore
Master of Science in Physics, University of the Philippines – Diliman
Bachelor of Science in Physics and Computer Engineering, Ateneo de Manila University

Angelita P. Tobias-Lozano
Data Scientist, JG Summit Holdings, Inc.
Doctor of Philosophy in Statistics (candidate), University of the Philippines – Diliman
Master of Science in Statistics, University of the Philippines – Diliman
Bachelor of Science in Statistics, Central Luzon State University

Noemi B. Torre
Assistant Professor, University of the Philippines – Diliman
Doctor in Mathematics, University of the Philippines – Diliman
Master of Science in Applied Mathematics, University of the Philippines – Diliman
Bachelor of Science in Mathematics, University of the Philippines – Diliman

Peter L. U
Associate Professor, School of Economics (SEC)
Ph.D. in Economics, Purdue University, West Lafayette, Indiana, USA
Master of Science in Industrial Economics, University of Asia and the Pacific
Bachelor of Science in Industrial Management Engineering, De La Salle University

Kimberly May M. Vallesteros
Program Director, Bachelor of Science in Data Science (BSDS)
Instructor, University of Asia and the Pacific
Master in Applied Business Analytics, University of Asia and the Pacific
Master of Science in Applied Mathematics, University of the Philippines – Diliman
Bachelor of Science in Mathematics, University of the Philippines – Diliman

Christian R. Vallez
Head of Business Strategy, Overmind
Director and Consultant, Arsokos, Corporation
Narrative Consultant, USAID-COMPETE
Chairman and Artistic Director, Arts and Culture Asia, Inc.
Instructor, University of Asia and the Pacific
Master in Business Economics, University of Asia and the Pacific
Master of Arts in Humanities, University of Asia and the Pacific
Master of Science in Information Technology, University of Asia and the Pacific
Bachelor of Science in Information Technology, University of Asia and the Pacific

Francis Adrian H. Viernes
Chief Data Scientist and Analytics Officer, Advance Tech Lending
Associate Director, Head of Data Analytics, Leechiu Property Consultants
Professional Masters in Data Science (Data Analytics) on-going, University of the Philippines – BGC
Master of Science in Finance, University of the Philippines – Diliman
Bachelor of Arts in Economics, Ateneo de Manila University

Jayson T. Yodico
Data Scientist, Union Bank of the Philippines
Lecturer, University of Asia and the Pacific
Master of Science in Data Science, Asian Institute of Management
Bachelor of Science in Industrial Engineering, University of Asia and the Pacific

Patrick S. Zeta
Faculty, School of Management (SMN)
Program Coordinator, Bachelor of Science in Business Administration (BSBA)
Master of Science in Management, University of Asia and the Pacific
Bachelor of Arts major in Humanities, University of Asia and the Pacific

INDUSTRY LECTURER / CONSULTANTS

Michelle A. Farcon
Vice President, Business Analytics Department under the Enterprise Business Intelligence Division, China Bank
Part-time Analytics Lecturer, University of Asia and the Pacific
Postgraduate Diploma in Financial Engineering, De La Salle University
Bachelor of Science in Mathematics major in Actuarial Science and Statistics, De La Salle University

Dominic Vincent D. Ligot
Founder & CTO, CirroLytix Research Services
Co-founder, Analytics Association of the Philippines (AAP)
Board of Trustees, Philippine Center for Investigative Journalism (PCIJ)
Founder & Director, Data Ethics PH
Senior Data Scientist, UNDP
Postgraduate, Clinical Epidemiology, Utrecht University
Postgraduate, Data-driven Marketing, Advanced Marketing Research, Cornell University – Johnson Graduate School of Management
Bachelor of Science in Business Administration, University of the Philippines – Diliman

Sherwin M. Pelayo
Chief Analytics Officer at Eclaro
Co-Founder, Analytics Association of the Philippines (AAP)
Bachelor of Science in Physics, Ateneo de Manila University

ADVISORY COUNCIL

Bernardo M. Villegas
Research Director of the Center for Research and Communication
Professor, University of Asia and the Pacific
Vice President, UA&PFI Board of Trustees
Doctor in Economics, Harvard University

Winston Conrad B. Padojinog
University President, University of Asia and the Pacific
President, UA&PFI Board of Trustees
Doctor in Business Administration, De La Salle University
MS Industrial Economics, University of Asia and the Pacific
BS Economics and Management, University of the Philippines – Visayas

Amado P. Saquido
Vice President for Academic Affairs, University of Asia and the Pacific
PhD in Business Administration (Finance), University of the Philippines – Diliman
MS in Information Management, Ateneo de Manila University
BS in Electrical Engineering, University of the Philippines – Diliman

Schedule

Classes which run for 3-hours are scheduled on weekday nights (6pm to 9pm), Saturdays morning (9am -12nn) or Saturday afternoon (1:30pm-4:30pm). Schedules are confirmed just before the beginning of each term.

Admission

Admission Criteria

Applicants to the UA&P MABA Program must hold a bachelor’s degree from an accredited institution with substantial professional experience in a particular domain. Having a quantitative background and occupying a management role are highly advantageous. Experience in a domain and managing projects are key factors to your success in the program.

Application Process*

1. The applicant must at least submit the following in soft-copy:

  • Application form. (Request a copy of the form)
  • Transcript of records or any copy of the applicant’s collegiate grades;
  • Curriculum Vitae or Resume; and
  • A 2-minute video

The other documents stated in the application form may also be submitted in soft copy. If not possible, may be submitted at a later date.

2. Instead of an exam, submit a two-minute video of the applicant talking about the analytics for a specific person e.g. leader (government official, policy maker, business (large, SME, NGO), worker, citizen, parent, student, etc.

3. Get interviewed by the MABA program.

4. Know the status of your application.

5. For successful applicants, enroll in Bridging Courses and attend Analytics Bootcamp.

*Current application process, subject to change when the COVID-19 pandemic situation eases.

Important Dates:

  • Information Session: April 2, 2022 | Saturday
  • Application Deadline: April 30, 2022 | Saturday
  • Interview Dates: May 7, 14, & 21, 2022 | Saturdays only     
  • Release of Application Result: May 28, 2022 | Saturday
  • Bridging Classes: June 4 – August 6, 2022 | Saturdays only
  • Analytics Bootcamp: August 13, 2022 | Saturday
  • Student’s Orientation: August 26, 2022 | Friday
  • Class Start Date: August 27, 2022 | Saturday

Contact Us

Master in Applied Business Analytics (MABA) Program
School of Management (SMN)
6th Floor, APEC Communications Building (ACB)
University of Asia and the Pacific
Pearl Dr, Ortigas Center, Pasig, 1605
businessanalytics@uap.asia

Dr. Ruel V. Maningas
Program Director
ruel.maningas@uap.asia

Ms. Marietta B. Galindes
Program Officer
marietta.galindes@uap.asia
8-637.09.12 local 309

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Get in touch

Address

Pearl Drive, Ortigas Center, Pasig City 1605, Philippines

 

Contact

Phone: (632) 8637-0912 to 26
E-mail: info@uap.asia