MSA PROGRAM DETAILS

Business analytics has been defined as the use of business intelligence and quantitative methods, including statistical analysis, forecasting/extrapolation, predicative modeling, optimization and simulation in the context of organizational decision making and problem solving.

This course provides an overview of business analytics process and important analytic techniques; data visualization, data mining, optimization, and simulation. Students are exposed to a variety of business problems in analytics (marketing, finance, operations).

Throughout the course, students will learn to model and analyze complex business decisions with various tools on spreadsheets to improve decision making across business functions.

This course covers the fundamentals of the usage of R and Python as programming languages, with emphasis on applications in business. Both R and Python have become languages of choice for business analysts due to being open source and containing a full array of software capabilities for data preparation, analysis, and visualization. Students will learn fundamentals of both languages and will be exposed to cutting edge packages and libraries to execute essential analytic tasks.

This course covers the concepts and techniques used to analyze and report structured data.

Students will learn tools and methods for understanding the data models supporting various business processes and for analyzing data from structured databases.

Multivariate Data Analysis focuses on the skills students need to be able to analyze and interpret multivariate data sets. Through real-world applications, students will learn to analyze data and interpret results using a variety of methods including data visualizations, multiple linear regression, analysis of variance models, and Chi-square models.

This course examines the concepts and approaches in Business Intelligence (BI) from a business user/analyst perspective.

Students will learn to use BI tools for creating applications and dashboards in the context of fact-based decision-making.

This course builds on the material from earlier courses in the program. It provides students with a chance to dive deeper into critical optimization, probability, and simulation modeling techniques useful in today's business environment. This course begins with a review of modeling basics, expands the students' exposure to optimization modeling techniques for both linear and nonlinear problems, and introduces simulation modeling using an industry-leading simulation software package. Students are exposed to a variety of business problems in analytics (marketing, finance, operations). Throughout the course, students will learn to model and analyze complex business decisions with various tools to improve decision-making across business functions.

Explores how (and when) various techniques can be used for mining data to uncover previously unknown patterns and gain insights. Students will mine large datasets from a variety of business areas and use their findings to support managerial decision-making.

Advanced coverage of techniques for mining text/web data to improve business decision making. Topics include text/web retrieval, classification/clustering, transforming text data into a structured format, text summarization, and social network analysis. Students will also be exposed to big data issues

Currently in development

Explores how the data warehouse provides the foundation for analytics within the enterprise. Topics include: dimensional models, design and creation of data warehouses and data marts, ETL process, and the extension of the data warehouse concept to “Big Data”

Exposes student to advanced and diverse applications of analytics in business. A combination of lecture, case discussion, problem solving, group projects, and completion of exercises will be used to further the knowledge and skills of students.

Capstone course for the MSA program. This course focuses on an application-based practicum project completed during the capstone term.

Students will combine the concepts and skill set learned throughout the program to navigate the analytics process and partner with an organization on a real business analytics project.

The course will blend lectures and assignments to help students obtain communication skills and project management skills needed to support their project and interactions with the client.