In today’s business environment, companies are awash in a sea of data. 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.
Analytics is a secondary concentration and should be taken with such functional concentrations as finance, marketing, health care or operations and supply chain management.
Analytics concentration students must take MGG 633, MGS 616, MGF 694 and two analytics elective courses from those listed under the electives tab:
View/search courses and descriptions.
Historically, managers have considered decision making as an art; something learned by trial and error; something based on creativity, judgment, intuition, and experience. This course gives you a structured way of attacking a wide range of real problems, using data-driven analysis to guide decision-making. We will consider how to think about and manage uncertainty and risk, how to translate data about the business into useful insights, how to put value on various courses of action, and how to generally make informed decisions. The main focus of the course will be on modeling decisions in the spreadsheet environment, illustrated by applications from operations, finance, marketing, and human resources. The approaches and techniques for decision-making are useful throughout the firm, both within functional areas and for the essential management challenge of working across functional boundaries.
Semesters offered: Spring 2018
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.
Fall 2018 (08/27/2018 - 12/07/2018)
|24089||F1S||LEC||TR||9:30 - 10:50 a.m.||Baldy 110||Gaia, Joana|
Spring 2018 (01/29/2018 - 05/11/2018)
|11567||S1S||LEC||TR||12:30 - 1:50 p.m.||Jacobs 112||Smith, Sanjukta Das|
|20884||S3S||LEC||MW||3:30 - 4:50 p.m.||Alfiero 102||Smith, Sanjukta Das|
|16630||S2S||LEC||TR||2 - 3:20 p.m.||Jacobs 112||Smith, Sanjukta Das|
This course utilizes "R," instead of Excel, as the computational tool. Students will learn how to download and process public data associated with economics, finance and accounting. Students will also learn how to apply "R" to various finance theories.
Semesters offered: Fall 2018
Pre-requisite: Two graduate courses, preferably Co
Fall 2018 (08/27/2018 - 12/07/2018)
|25037||F1F||LEC||M||5 - 7:50 p.m.||Jacobs 214||Yan, Yuxing|
For this concentration, you need to have foundational programming knowledge or to have taken non-credit bridge courses, either prior to beginning your MBA or during the summer of your first year, to give you a broad introduction to foundational analytics methods (e.g., SAS, R). You may select any two courses from the following list, or an alternative course approved by the chair of the MBA/MS program committee:
The School of Management does not offer courses for these subjects. Faculty will recommend summer reading or materials.