Analytics Concentration

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.

Be Career Ready

  • Gain in-depth knowledge to model and solve complex business problems
  • Model the managerial decision-making process through advanced Excel techniques
  • Acquire career-defining statistical skills using industry-leading applications, specifically SAS, R and Python
  • Apply marketing analytics to consumer behavior data for smarter decision-making
  • Develop the skills needed to perform risk analysis and strategic investment management
  • Understand how analytics solve the problems of a complicated health care delivery system
  • Become a technology data analytics leader by learning database management and decision support systems
  • Learn the importance of data stewardship through data management methodologies

Analytics is a secondary concentration and should be taken with such functional concentrations as finance, marketing, health care or operations and supply chain management.

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Analytics concentration students must take MGG 633, MGS 616, MGF 694 and two of the following data analytics electives:

MGF 637LEC Financial Modeling

In this course, students will use financial econometric models to analyze problems of model specification, estimation, analysis and forecasting commonly faced by analysts in financial markets. The course materials cover the measurement and estimation of asset returns, earnings, macroeconomic data, risk and related applications in financial data analysis and visualization. Topics include regression analysis of time series/ARIMA models, multiple regression specifications and models of asset volatility including ARCH and GARCH. Throughout the course, students will use the statistical functions of the R programming language to analyze, model and forecast a variety of financial data.

Credits: 3.00
Semesters offered: Fall 2018 | Spring 2018


MGF 696LEC Portfolio Theory and Strategy

The course covers sophisticated approaches to investing and it has an introduction and three main parts. The introduction covers measures of performance and risk and methods to calculate them in closed form or from historical data. The first part of the course covers investment strategies across several asset classes, from traditional ones such as value or growth investing to strategies employed by hedge funds, such as arbitrage, option trading and other quant strategies. The second part of the course addresses portfolio construction, from assessing a utility function to the investor to constructing an optimal portfolio maximizing that utility. Investor types covered are individuals saving for retirement, speculators, university endowments or foundations, or pension funds. Finally, the last part of the course addresses the topic of risk measurement and management, with an emphasis of risks faced by decentralized organizations, such as funds of funds, foundations, or pension funds.

Credits: 3.00
Semesters offered: Fall 2018
Co-Requisite: MGF 633


MGS 613LEC Database Mgmt Systems

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.

Credits: 3.00
Semesters offered: Fall 2018


MGO 619LEC Business Forecasting

This course is devoted to delivering, constructing, and implementing business forecasting analytical models and systems (with data) that are capable of enhancing decision making and providing decision support for managerial and policy decisions at the firm, industry, and country levels. It is emphasized that applications of predictive methodology and empirical analysis are an integral part of the course. Both methods and results provide solutions to problems and insights to decision makings.

Credits: 3.00
Semesters offered: Spring 2018


Spring 2018 (01/29/2018 - 05/11/2018)

Reg. Num. Section Type Topic Days Time Location Instructor
24478 S1O LEC MW 11 a.m. - 12:20 p.m. Norton 216 Lin, Winston T

MGO 636LEC Supply Chain Analytics

This course focuses on design, modeling and optimization of supply chain networks. Topics covered include: global supply chain strategy formulation, performance metrics, new forecasting models applicable for supply chain contexts, newsvendor models for capacity and aggregate planning, models for location and design of supply and distribution entities, inter-organizational planning, advanced planning systems, multi-echelon inventory analysis, distribution requirements planning (DRP) systems, joint transportation-inventory models, and pricing and revenue management techniques.

Credits: 3.00
Semesters offered: Fall 2018


Fall 2018 (08/27/2018 - 12/07/2018)

Reg. Num. Section Type Topic Days Time Location Instructor
12293 F10 LEC M 6:30 - 9:10 p.m. Alfier 104 Wang, Xiaoqiang
12519 F20 LEC MW 3:30 - 4:50 p.m. Jacobs 106 Wang, Xiaoqiang

 • 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

Graduate Programs Office
School of Management
University at Buffalo
203 Alfiero Center
Buffalo, NY 14260-4010

Tel:  716-645-3204
Fax: 716-645-2341
som-apps@buffalo.edu

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