Business Analytics - GR (BUAN)


BUAN 505  Information Analytics and Visualization in Decision Making  3 Credits (3,0)

One of the most potent models of the decision process is the OODA Loop -- that we Observe, Orient, Decide, and then Act. Key to this or any other control and decision (or cybernetic) process is that vast quantities of raw sensory data about the outside world must be processed, abstracted, and then presented in contrast and conjunction with the knowledge previously generated and retained. This two-step process -- the reduction, analysis, filtering and abstracting of data into knowledge, and its presentation in formats and fashions that support the decisions that must be made -- is the subject of this course. The relationships between such analysis and visualization will be examined in the context of business and organizational decision-making and decision support systems concepts.

BUAN 522  Business Analytics, Social Network and Web Analytics  3 Credits (3,0)

Analytics is the application of techniques to identify important observations and patterns in data. Analytical techniques can be used to overcome the practical challenges presented by data, such as the challenges presented by data volume, variety, velocity, and other properties. This includes application of techniques of data reduction, filtering and analysis in order to identify, measure and assess key business indicators. This course focuses on the business rationale for and application of analytics including exploration of how decision-making processes can and should be driven by the results of well-crafted analytics processes. In particular, the course focuses on both the need for organizations to more fully understand, appreciate and exploit so-called "soft" or "unstructured" data -- the things human beings say to each other, in uncontrolled and unformatted ways, on various social media. Search histories and other "temporary" data, not normally revealed by traditional search engines, will also be examined.

BUAN 523  Data Mining for Business Analytics  3 Credits (3,0)

Data mining is both finding the right data in one's file systems or data warehouses, by applying smarter search and filtering criteria, as much as it is the reduction, analysis and presentation of that data in meaningful ways. While many of these techniques are statistical in nature, many rely on applied artificial intelligence algorithms - so-called "machine learning" - to help the organization's managers, accountants and doctors in "discovering" new knowledge in the sea of data that they already have, but cannot digest without significant software help.This course surveys methodologies useful for data mining for business analytics and guides the student in identifying the data mining process from the data exploration phase to the different predictive techniques.

BUAN 524  Applied Business Intelligence and Analytics  3 Credits (3,0)

Business intelligence (or BI) and analytics is both a process and a product. The product is the timely, precise, high-value and actionable business insights that management needs to make decisions. The process is the gathering, collating, analyzing, and assessing of many different kinds of information that lead to those insights. Business intelligence processes and analytics products can have a profound impact on corporate strategy, performance and competitiveness; and much like intelligence processes and products in the military and national security arenas, BI and analytics can have positive or negative impacts upon the organization depending upon how it is done and how it is used (or misused). This course presents students with both the theoretical concepts and practical applications of BI and analytics, and examines some predictive analytics techniques using SAS(c).