Master of Science in Business Analytics
Business Analytics refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning by using data and statistical methods. A variety of industries are in need of professionals who can take on positions of responsibility for collecting, analyzing and interpreting data in order to make sound strategic business decisions.
The MSBA program seeks to fill the talent gap in the area and to prepare graduates for this fast-growing field by developing students' critical skills in data- and model-driven management decision-making in the context of a firm's strategic vision. The program, which begins annually in September, consists of 10 three-credit courses (seven are required and three are electives). The program is designed to be completed either in one year's time (full-time) or over two years (part-time). Students may opt to use their elective courses to earn a specialization that is tailored to their career interests. Available specializations include: Artificial Intelligence, Healthcare, Marketing Analytics, and, for those who have an undergraduate degree in Accounting or the equivalent, Accounting.
Requirements
| Code | Title | Credits |
|---|---|---|
| BUAN 6500 | Business Analytics 1 | 3 |
| BUAN 6505 | Python for Business Analytics | 3 |
| BUAN 6510 | Databases for Business Analytics | 3 |
| BUAN 6530 | Business Forecasting and Predictive Analytics 1 | 3 |
| BUAN 6540 | Business Intelligence | 3 |
| BUAN 6545 | Machine Learning for Predictive Analytics | 3 |
| BUAN 6999 | Capstone: Business Analytics Applications | 3 |
| Select three elective courses in Business Analytics 2 | 9 | |
| Total Credits | 30 | |
| 1 | Designated research course. |
| 2 | Students are required to complete an additional 9 credits (3 courses) of graduate work at the 6000-level. Students may choose elective courses either to fulfill the requirements of one of the specializations listed below, or to enrich their background in an area of interest. Please note: Students must complete the appropriate prerequisite(s) before taking 6000-level graduate courses chosen as MS Business Analytics program electives. |
Accounting Specialization
To be eligible to pursue this specialization, students must have an undergraduate degree (BS or BA) with a major in accounting or the equivalent. The equivalent of an undergraduate degree in accounting includes the successful completion of: intermediate accounting (six credits), advanced accounting (three credits), cost accounting (three credits), auditing (three credits), and U.S. taxation (three credits). Deficiencies will be handled on a case-by-case basis.
To complete a specialization in Accounting, students will take any three graduate Accounting or Taxation courses at the 6000-level for their required electives. Students trying to meet educational requirements for CPA certification are encouraged to consult with the Coordinator of Graduate Accounting Programs in selecting their graduate Accounting or Taxation courses.
Artificial Intelligence Specialization
To complete a specialization in Artificial Intelligence, students will take three courses involving any combination of ISOM 6550 and/or ISOM 6900 courses. ISOM 6550 may be taken, at most, once for credit for this specialization. The topics course ISOM 6900 may be taken multiple times for credit, up to three times if ISOM 6550 is not taken, or up to two times if ISOM 6550 is taken, as long as the topics offered are different. Topics courses are expected to be offered on sports analytics, deep learning, classic AI, and more.
| Code | Title | Credits |
|---|---|---|
| ISOM 6550 | Business Analytics and Big Data Management | 3 |
| or ISOM 6900 | Contemporary Topics Seminar | |
| ISOM 6900 | Contemporary Topics Seminar | 3 |
| ISOM 6900 | Contemporary Topics Seminar | 3 |
| Total Credits | 9 | |
Healthcare Specialization
To complete a specialization in Healthcare, students will complete the following as their required electives:
| Code | Title | Credits |
|---|---|---|
| Select three courses from the following: | 9 | |
| Advanced Healthcare Policy | ||
| Healthcare Economics and Marketing | ||
| Finance and Quality Management in Healthcare Organizations | ||
| Information Technology for Healthcare Improvement | ||
| Total Credits | 9 | |
Marketing Analytics Specialization
To complete a specialization in Marketing Analytics, students will complete the following courses as their required electives:
| Code | Title | Credits |
|---|---|---|
| MKTG 6520 | Marketing Research | 3 |
| MKTG 6580 | Multivariate Analysis for Consumer Insights | 3 |
| MKTG 6900 | Contemporary Topics | 3 |
| or MKTG 6590 | Experimental Research | |
| Total Credits | 9 | |
Note: MKTG 5400 or its equivalent is a required prerequisite for all upper-level marketing courses.
MBA and MS in Business Analytics Overlap
The MBA with a concentration in Information Systems/Business Analytics (MBA-IS/BA) is a generalist degree that covers all relevant topical areas for a business professional, and gives the students the opportunity to concentration on, but not major in, Information Systems. Immediately after completion of the MBA-IS/BA, students sometimes wish to further their graduate study in Business Analytics. Interested students then may apply for admission to the MS in Business Analytics and, once accepted, can earn the degree by completing an additional 6 courses drawn from the MS in Business Analytics curriculum. Courses are selected in advisement with the Director of Graduate Programs. Students are encouraged to seek individualized advisement well before completing the MBA-IS/BA.
BUAN 5400 Applied Business Statistics 3 Credits
Using spreadsheet software, this hands-on course teaches a variety of quantitative methods for analyzing data to help make decisions. Topics include: data presentation and communication, probability distributions, sampling, hypothesis testing and regression, and time series analysis. This course uses numerous case studies and examples from finance, marketing, operations, accounting, and other areas of business to illustrate the realistic use of statistical methods. Previously QA 0400.
BUAN 5405 Python Fundamentals 3 Credits
This course is an introduction to Python, with an emphasis on general programming concepts (structure, logic, data, etc.) that apply to just about any general purpose programming language. Starting with a review of fundamental programming concepts, the course uses short lessons, quizzes, and coding challenges to cover the basics of how Python is used in a professional Business Analytics setting. The course concludes with a final project designed to demonstrate proficiency. Previously BA 0405.
BUAN 5410 Analytics Programming for Business 1.5 Credits
This course focuses on quantitative modeling and analyzing business problems using spreadsheet software, such as Excel and its add-ins. Topics include descriptive analytics, visualizing and exploring data, predictive modeling, regression analysis, time series analysis, portfolio decisions, risk management, and simulation. Business models relevant to finance, accounting, marketing, and operations management are set up and solved, with managerial interpretations and "what if" analyses to provide further insight into real business problems and solutions. Open to MS Management students only. Previously BA 0410.
BUAN 6500 Business Analytics 3 Credits
This course introduces basic skills necessary for business analytics such as data analysis using basic statistics, data visualization and summarization, descriptive and inferential statistics, spreadsheet modeling for prediction, linear regression, risk analysis using Monte-Carlo simulation, linear and nonlinear optimization, and decision analysis. Microsoft Excel is used as the platform for conducting analyses and performing statistical calculations. Previously BA 0500.
BUAN 6505 Python for Business Analytics 3 Credits
Prerequisite: BUAN 5405 or placement exam.
In this course, we introduce Python as a language and tool for collecting, preprocessing, and visualizing data for business analytics. Since Python is one of the most popular programming languages, along with R, in data mining and business analytics, its fundamental programming logic and knowledge is essential for students to apply in data mining and to succeed in the job market. Specifically, this course focuses on the data-engineering phase, which includes collecting, preprocessing, and visualizing data, with respect to applications in business modeling, optimization, and statistical analysis. In addition, a number of mini projects will be used as vehicles to cover the main applications of data analytics, including recommender systems, text analytics, and web analytics. Previously BA 0505.
BUAN 6510 Databases for Business Analytics 3 Credits
This course introduces databases and data management in three parts. The first part covers basic database fundamentals. The second part is a hands-on introduction to Structured Query Language (SQL) for defining, manipulating, accessing, and managing data, accompanied by the basics of data modeling and normalization needed to ensure data integrity. The course concludes with a comprehensive database project that gives each student the opportunity to integrate and apply the new knowledge and skills learned from this class. Advanced topics such as distributed database systems, data services, and NoSQL databases are also discussed. Previously BA 0510.
BUAN 6530 Business Forecasting and Predictive Analytics 3 Credits
Prerequisite: BUAN 5400 or placement exam.
This course introduces analytical techniques used for decision-making under uncertainty. Topics include time series and other forecasting techniques, such as Monte Carlo simulation, to assess the risk associated with managerial decisions. Specifically, we will cover data collection methods, time dependent models and analysis, advanced solver, time series techniques, exponential smoothing, moving averages, and Box-Jenkins (ARIMA) models. Application examples include financial models - stock prices, risk management - bond ratings, behavior models - customer attrition, customer likes/dislikes, buying patterns - propensity to buy, politics - identify swing voters, and sales. Previously QA 0500.
BUAN 6540 Business Intelligence 3 Credits
Prerequisites: BUAN 6500, BUAN 6510, BUAN 6530.
This course will change the way students think about data and its role in business. Increasingly, managers rely on intelligent technology to systematically analyze data to improve their decision-making. In many cases, automating analytical and decision-making processes is necessary because of the large volume of data and the speed with which new data are generated. In this course, we will examine how data warehousing, modeling, and visualization can be used to improve managerial decision making. Previously BA 0540.
BUAN 6545 Machine Learning for Predictive Analytics 3 Credits
Prerequisites: BUAN 6505, BUAN 6530.
This course provides an advanced understanding of the practices of machine learning techniques, with a special focus on business applications. To assure practical relevance, the emphasis of this course is on the applications of techniques and tools realizing machine learning interms of business analytics. The course is organized following the Cross-Industry Standard Process for Data Mining (CRISP-DM) and all learned techniques are applied in a semester-wide project. Python is introduced and illustrated through a series of tutorials and case studies. Students are expected to actively participate in the course deliverables through independent assignments, lab work, and group projects. Previously BA 0545.
BUAN 6999 Capstone: Business Analytics Applications 3 Credits
Prerequisites: BUAN 6540, BUAN 6545.
This capstone course for the MS Business Analytics program is to be taken in the last term before graduation. The purpose is to apply and integrate knowledge and skills learned in the program (statistics, modeling, data management, data mining, etc.) to a live data analytics project. The course is project-based, with students collaborating on their work under the guidance of faculty members. Application areas and format of the projects may vary, depending on faculty, dataset, and budget availability. However, the work should be rich enough to demonstrate mastery of business modeling and technology, with each student making a unique, demonstrable contribution to completion of the work. Previously BA 0590.
ISOM 5400 Business Operations 3 Credits
This course introduces basic concepts and tools relevant to operations and supply chain management, including process mapping, quality management, decision analysis, capacity planning, supply chain management, project management, and operations strategy. Case studies are used to link the concepts and models to real-world business applications. Previously OM 0400.
ISOM 6500 Information Systems and Database Management 3 Credits
This course introduces the basic concepts and tools relevant to information systems and database management, and their enabling roles in business strategies and operations. Case studies are used to facilitate discussions of practical applications and issues involving strategic alignments of organizations, resource allocation, integration, planning, and analysis of cost, benefit and performance in light of the big data challenges. Specific emphases involve database design and implementation and emerging strategies and technologies such as business intelligence, big data management, web security, and online business analytics. Previously IS 0500.
ISOM 6520 Project Management 3 Credits
Prerequisite: ISOM 5400 or ISOM 6500.
This course explores the process and practice of project management. Topics to be covered include project lifecycle and organizations, teambuilding and productivity, task scheduling and resource allocation, and progress tracking and control. Cases will be used to consider the implications for change management, consulting, IT implementation, and other related disciplines. Small team projects and experiential exercises will also be used to provide an active learning environment. This course is designed to count toward professional project management certification. Previously IS 0520.
ISOM 6550 Business Analytics and Big Data Management 3 Credits
Prerequisites: BUAN 6540, BUAN 6545.
This course will survey state-of-the-art topics in Big Data, looking at data collection (via smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting structured data from unstructured databases, systems issues (exploiting multicore, security), analytics (machine learning, data compression, efficient algorithms), data visualization, and a range of applications. Each of these five modules will introduce broad concepts as well as provide the most recent developments in the area. Previously IS 0550.
ISOM 6900 Contemporary Topics Seminar 3 Credits
This course draws from current literature and practice on information systems and/or operations management. The topics change from semester to semester, depending on student and faculty interest and may include: project management, e-business, management science with spreadsheets, e-procurement, executive information systems, ethics, and other socioeconomic factors in the use of information technology. Previously IS 0585.
ISOM 6990 Independent Study 3 Credits
This course provides an opportunity for students to complete a project or perform research under the direction of an Information Systems and Operations Management (ISOM) faculty member who has expertise in the topic being investigated. Students are expected to complete a significant project or research paper as the primary requirement of this course. Enrollment by permission of the ISOM Department Chair only. Previously IS 0598.