Business Analytics Graduate Certificate

This course employs extensive use of data and statistical methods to support and improve organizational decision-making. Topics include data visualizations, descriptive statistics, probability distributions, sampling, confidence intervals, hypothesis testing, regression analysis, and the use of computer software for statistical applications. The primary focus will be on the flexibility of the analysis, and the ability to present the results in an intuitive and understandable manner for greater organizational impact. The ethical issues related to big data will also be discussed.

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.

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

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.