MBA in Business Analytics

Foundational principles making computers learn, plan, and solve problems autonomously; and driving modern intelligent agents on real-world applications for contemporary problems, such as deep learning, data flows, and autonomous driving.

This course introduces fundamentals about data and the standards, technologies and methods for organizing, managing, curating, preserving, and using data. The course will teach students the use of software such as Python for data manipulation, analysis and visualization. The course also incorparates broader issues surrounding data, including technologies, behaviors, organizations, policies, and society. Special attention will be given to ethical issues surrounding data, soical and historical perspectives on data with ethics and policies to help students develop a workable understanding of current ethical issues in data science. Finally, the ethical issues will be addressed that arises throughout the lifecycle of data - from collection to storage to analysis and application.

To compete in a data-driven world, data analytic skills and database skills are key. Before data is analyzed, correct data first needs to be chosen and pulled from a database within your organization or your client's organization. While the term big data is influenced by the rise of unstructured data (no-SQL database), structured data (SQL/relational database) remains a large and important component because structured data is driven by business processes and workflows. This course mainly focuses on process-driven/structured data and a relational database. This course is not designed to develop database building skills. A large focus of this course is placed on an understanding of database schema (or how business data is collected in relation to other business data) and SQL coding techniques for selecting the right data for the purpose of further analysis.

This course introduces students to basic mathematical and statistical methods and models, as well as their software applications for solving business problems and/or in making decisions. Included topics are linear regression, analysis of variance, introductory time series analysis & forecasting and several advanced applications of the general linear model. This course uses numerous case studies and examples from economics, finance, marketing, operations and other areas of business to illustrate the realistic use of statistical methods.
Prerequisite: Take BUAN-651

Visualizations are graphical depictions of data that can improve comprehension, communication, and decision making. This course is an introduction to the principles and techniques for data visualization. In this course, students will learn visual representation methods and techniques that increase the understanding of complex data and models. Emphasis is placed on the identification of patterns, trends and differences from data sets across categories, space, and time.
Prerequisite: Take BUAN-651

In this course, students learn the concepts and development of analytical model building as used in global supply chain decisions. Topics include forecasting and inventory management, sales and operations planning, transportation, logistics and fulfillment, purchasing and supply management, supply chain risk management, etc. in manufacturing, trade and service industries. Students learn to define the right data set, ask the right questions to drive supply chain efficiency and business value and use the right models and tools to develop data-driven decisions. Software packages such as Python will be utilized.

Pricing and revenue analytics is a set of practices and tools that firms use to optimize product & service choices, pricing, and promotion strategies. Students will be able to identify and develop opportunities for revenue optimization in different business contexts including the retail, telecommunications, entertainment, financial services, health care, manufacturing, among others. Adoption of these modeling techniques in the on-line advertising, online retailing, and online markets will also be discussed.
Prerequisite: Take BUAN-651

The objective of the course is to learn about FinTech - the technologies that are disrupting traditional financial services - and how it is changing areas such as mobile payments, trading, lending, capital markets, and asset management. The course will survey emerging issues in FinTech, enabling students to understand key transformations happening in the financial services industry and the trends that will impact the industry in the future.

Course Title - Artificial Intelligence and Financial Technology in Financial Markets. We will cover a variety of applications of AI and Fintech in the financial markets, including streamlining credit and loan transactions, automating and personalizing financial services, predictive analysis for investment and risk management, fraud detection and regulatory compliance, as well as direct and cost-effective fundraising. Students will create their own crowdfunding projects through ICOs and NFTs.

This course explores the strategic role of analytics and business intelligence in an organization. Students will learn to evaluate the strategic environment of an organization, use strategic models to formulate a strategy and the implementation of that strategy. The course will then emphasize the interplay between analytics and strategic considerations in an organization. Students will learn the practicual application of analytics to formulate an organization's strategy and reversely the influence of the organization's strategy to nature of the analytics within the organization.