Business Analytics Online Master's Degree Program

In this course students learn to differentiate relational and non-relational databases, and to design a database to an organization's requirements. Preparing raw data for import into a database, using queries to manipulate data, and developing reports to meet stakeholder needs, and database integrity and security are also covered.

Students learn to create and use scripts to access, acquire, prepare, and transform data, including structured and semi-structured data, and to define and detect patterns in unstructured data to demonstrate how real world problems can be answered with data.

In this course students learn about data types and how to perform pre-processing activities including cleaning, integration, reduction, and transformation. Use of appropriate techniques to analyze and model data, such as classification, decision trees, association rules, and clustering, and the causes and methods of detecting outliers are also covered. Students propose additional applications for data mining based on current trends/research.

In this course students learn about deep learning, machine learning, and artificial intelligence, and compare supervised and unsupervised learning. Machine learning workflows and the challenges associated with machine learning, such as bias and heteroscedasticity, are considered. Students evaluate models, and examine uses for machine learning and artificial intelligence. Natural Language Processing is also addressed.

Decision-making in any organization cannot be separated from financial considerations, and those involved with strategic planning and operations need to understand the impact their work has on the organization's financial performance. Managers must understand the organization's financial models in order to make a meaningful contribution to the overall success of the organization. Students will focus on using financial information rather than creating it and will use case studies and simulations to experience low-risk financial decision-making.

The operation of an organization focus on the transformation processes used to produce goods or provide services. Develop the skills needed to ensure the ongoing strategic contribution of a firm's operations to its competitive position. Investigate design thinking and the impact it can have on the complex processes underlying the development and manufacture of products as well as the creation and delivery of services. Topics include process analysis and cross-functional and cross-firm integration as part of a strategic vision.

Students learn organization analysis from a holistic perspective. Financial reports and financial ratios are the basis for traditional organizational analysis and builds from that foundation into the analysis of customer, supplier and employee metrics. Focus is on the Balanced Scorecard and other holistic approaches.

This course covers the foundations of Data Management for Business Analytics. Students examine and explore the value of information, as an asset and as a liability, and organize and assess its value in an information- driven organization dealing with the challenges of Big Data, Open Data and privacy protection legislation.

Students learn to create powerful reporting tools, to forecast data behavior, and to explore its use in business. This class has a hands-on approach, developed in the context of the application of analytics to business, allowing students to develop the skills necessary to create relevant tools for data-driven organizations. All hands-on work assumes the existence of a technology infrastructure, and no prior knowledge on how to install or maintain the software used in the labs is required.

Students apply the business analytics skills to specific business areas. Students will explore techniques and develop tools that model consumer behavior, supply and demand, and financial performance, in order to predict data evolution in different conflicting scenarios. Students will also apply business analytics to HR decision making such as recruiting, performance measurement, or compensation.

Students will integrate learning and competencies from the Business Analytics program into a single data-based project.? Given a data set, students will ask such questions as why is the data organized as it is, what are the benefits and limitations of the data set, what appropriate visualization elements should be developed, and what business recommendations should be made.