Every day, a tremendous amount of information is created, modified, and stored digitally.
Companies are racing to utilize this information, now called “big data”, in hopes of future-proofing their business and making smarter decisions.
Our PSM Business Analytics (Biztics) degree is the first program of its kind in Korea.
Combining both education and training, it prepares students to become analysts and effective decision makers.
In Biztics, students learn professional analysis techniques and develop a mastery of statistics, data mining, and analysis programming. Supplemental courses on market analysis, management strategy, information management, and more are also available.
Additionally, UNIST leverages its strong relationships with overseas research institutes and scholars, creating new opportunities for education at the highest level.
Get informed, stay knowledgeable, and learn to interpret this rapidly changing market for success in corporate management.
Become a business analysis expert by joining the UNIST Business Analytics program.
This course is to help a student to understand what business analytics is about, how it can help managers to make better decisions and an organization perform better, and what kind of capabilities need to be addressed for an organization to be analytical. It also describes 5 success factors (data, enterprise, leadership, targets, and analysts) for analytical capability and the best way to strengthen them.
BAT511Introduction to Data Mining
Data mining is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems. The basic data mining techniques and their use in a business context will be addressed. Furthermore, an advanced topic in data mining (i.e. process mining) will also discussed in the class.
BAT512Advanced Techniques for Data Mining
Advanced data mining is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems. The Advanced data mining techniques and their use in a business context will be addressed.
This course will provide students with analytical and decision making skills through a variety of topics in statistics and optimization modeling. Underlying theory for statistical analysis and its business applications will be emphasized. This helps students evaluate and handle business situations with statistics in mind. As a result, students will be well prepared to describe and analyze data for decision makings in business fields such as marketing, operations, and finance.
BAT514Business Modeling and Decision Making
This course will enable students to build deterministic and probabilistic models of business problems that lead to making better managerial decisions. Students will acquire the necessary skills to analyze complex business situations, develop mathematical models of those situations, explore and prioritize alternative solutions through formalized approaches, and do “what if?” sensitivity analysis to gain insight into why the chosen solution makes business sense. Among the topics covered will be linear and integer programming, dynamic programming, non-linear optimization, Monte Carlo simulation, decision analysis and utility theory, and multi-criteria decision making.
This course aims to teach students programming techniques for managing, and summarizing data, and reporting results.
This course is an introduction to database systems that manage very large amounts of data. One of the popular approaches in database management is relational model, which uses a two-dimensional table as its primary structure. The relational model underlies the major commercial database systems. We cover relational design using the ER (Entity-Relationship) model and UML (Unified Modeling Language), and SQL (Structured Query Language), the standard query language for relational databases, will be learned and experienced. Another focus of this course will be data preparation for further business analytics. It includes the use of SQL along with statistical and data mining tool (e.g., SAS) and multi-dimensional data extraction from data warehouse.
BAT517BPM and Process Mining
BPM/Process Mining course focuses on so-called “process-aware” information systems. The first part of the course focuses on the modeling and implementation of BPM (Business Process Management). Different languages and systems are presented. Emphasis is on the control-flow and resource perspective. The second part of the course focuses on the analysis of workflows/business processes. Different types of analysis such as business process simulation, workflow verification, etc. will be considered. Furthermore, this course teaches students the theoretical foundations of process mining and exposes students to real-life data sets to understand challenges related to process discovery, conformance checking, and model extension.
BAT523Decision Making in Strategic Management
Firms’ allocation of funds, resources, and time for competitive advantage should be aligned with their strategy. This course focuses on analytic methods for strategic decision making. At different levels of strategic management, various analytic methods will be introduced with examples and case studies. This course also covers basic contents of strategic management to help students understand the analytic methods.
In this course, students will study how information is produced and managed in enterprises. Main topics discussed include: the principles of information management; information management technologies; techniques to analyze information needs and use; and the social and ethical context of information management.
This course develops fundamental knowledge and skills for applying advanced analytical methods to help make better decisions. By using techniques such as mathematical modeling to analyze complex situations, students will learn how to make more effective decision and build more productive systems based on the intelligent use of data. Topics include optimization, statistics, forecasting, and probabilistic analysis.
BAT526~8Topics in Business Analytics I~III
This course will provide students with an opportunity to study how Business Analytics knowledge and techniques are applied in various fields. Possible topics include: Financial Analytics, Web Analytics, Healthcare Analytics, Text Mining, Social Analytics, and so on.
BAT551Business Analytics Practicum
In this course, students will not only have a chance to hear from CEOs, but also learn analytics-related techniques, such as data visualization, presentation skills, and consulting skills.
In order for an opportunity to apply their learning to a real field, students must complete a Capstone Project in collaboration with a company, under the supervision of an appointed advisor.The project scope is decided by discussion with the advisor.
Professional Science Master
The Professional Science Master’s (PSM) degree is science-plus, combining rigorous study in science or mathematics, with the added real-world benefit of skills-based coursework in management, policy, or law. The PSM started in 1997, with only 14 programs available in America. Now, as of January 2018, more than 335 programs from 165 institutions are developed and utilized throughout America, Canada, Australia, and Asia. GSIM’s PSM programs provide a set of curricula relevant to business fundamentals, financial and organizational behavior with an emphasis on science, technology, and management. The Energy Commodity Trading and Financial Engineering (ECTFE) program and Business Analytics (Biztics) program at UNIST GSIM are the first approved PSM programs across all of Asia, including Korea.https://www.professionalsciencemasters.org/
|National Information Society Agency||2014.02.20||Training|
|Korea Culture & Tourism Institute||2014.06.27||Competition|
|Korea Bigdata Society||2014.09.18||Forum|
|Ministry of Science and ICT||2014.11.07||Competition|
|Korea Assembly Office||2014.12.17||Forum|
|UN Global Pulse(MICT)||2015.06.24.~06.29||Competition|
|Korea Culture & Tourism Institute||2015.08.28||Competition|
|Ministry of Land, Infrastructure and Transport||2015.09.23||Competition|
|Seoul National University||2015.10.13.~10.15||Forum|
|Korea Meteorological Administration||2015.10.20||Competition|
|Competition of Startup with Public Data||2015.10.29||Competition|
|Competition of Startup with Public||2015.11.23||Competition|
|The Knowledge Management Society of Korea||2014.11.28||Forum|
|The Knowledge Management Society of Korea||2015.11.20.~11.21||Forum|
|The Korea Association for Information Society||2016.11.04||Forum|
|Ministry of Oceans and Fisheries||2017.06.01||Competition|
|University of Liechtenstein(ERCIS)||2014.01.24||Project joint|
|University of Liechtenstein(ERCIS)||2016.02.21.~02.26||Training|