In today’s business environment, companies are awash in a sea of data. But how do you make sense of it?
Analyzing data using modern technology, sophisticated statistical tools and good old-fashioned storytelling helps firms make smart business decisions. The MBA analytics concentration provides foundational quantitative and analytical skills paired with application in specific management areas.
MBA Analytics concentration students must take two of the following data analytics electives:
This course covers the models of corporate finance and investments. We will cover how to use spreadsheet programs, such as Microsoft Excel, to build and analyze financial models. The financial models we will review are pro forma financial statement analysis, cost of capital modeling, portfolio management modeling, etc. Also, other empirical models of corporate finance and asset pricing will be introduced, such as time series properties of stock return etc. Although MGF633, MGF 641, and MGF 642 are not prerequisite for this course, taking those courses simultaneously will be plus.
Semesters offered: Fall 2017 | Spring 2018
This course focuses primarily on stock investment strategies for active investors in inefficient markets and secondarily on portfolio strategies in efficient markets. Students will gain an understanding of the technical analysis of price movements, psychology of market participants, and multi-factor expected return models. Typical investment approaches such as value and growth investing are thoroughly examined.
Semesters offered: Fall 2017
Co-Requisite: MGF 633
Marketing Analytics will focus on how to use data analytics to analyze marketing problems for better managerial outcomes with a specific focus on quantitative techniques and hands-on learning utilizing software such as SAS and R. Today, companies are inundated with data as the cost of gathering, storing, and processing data is becoming more economical. The above is especially true for marketing data. However, knowing how to interpret marketing data is challenging. Firms are increasingly using data driven analytics to inform their decision making. The objective of this course is to equip students with skills to analyze data (especially marketing data) so as to enable superior decisions.
This course is designed to provide students with a basic understanding of database management systems (DBMS) and the skills needed to design and implement a relational database. Students will be introduced to data modeling concepts, modeling tools, the process of transforming conceptual models into relational database designs, and finally the steps needed to implement those designs. Emphasis is placed on Entity-Relationship diagramming, data normalization, database administration, and data definition, data manipulation and query development using Structured Query Language (SQL). Other topics covered include: object-oriented databases, database security and integrity, web/database integration, application development in a Client/Server environment, distributed databases, data warehousing, data mining and knowledge management via the Internet to support electronic commerce. Readings, lectures, interactive case assignments and a database design project reinforce the role of DBMS in supporting organizational systems, transaction processing and decision support applications.
Semesters offered: Fall 2017
This course teaches the technical and managerial skills needed in developing predictive analytics applications which are used by customer-centric corporations - retail, financial, communication, and marketing groups - to help make decisions involving complex systems. The course concentrates on a set of well-known predictive analytics methods to support business decision making. Topics such as association rule mining, decision trees, neural networks, regression analysis and cluster analysis are covered in great depth. Extensive hands-on experience using software such as SAS Enterprise Miner is provided.
Semesters offered: Spring 2018
• STA 503 Linear Regression (SAS)
• Other graduate course(s) may be approved by the chair of the MBA/MS Committee as an elective.
Note: Not all electives above are offered every semester