MSBA/MSF Dual Degree (Archive 2018-2019)

1.00

SBS 700 is the first required course in Suffolk's graduate programs. The course is based on the precepts of experiential learning. Based on the idea that people learn best by participating in meaningful activities, this course provides students with the opportunity to learn about and experience first-hand the many complexities of business and the role of top managers. To accomplish this, students will work in small groups as they take on the roles of top managers in a hands-on behavioral simulation.

MSF and MSFSB students only;

1.00

This is a boot camp-style course which introduces students to the basic concepts of math, statistics, accounting, and finance. Given the technical nature of modern finance, this course is designed to prepare students for the challenges of taking advanced finance courses. The course is based on lectures, problem solving, and discussion of concepts.

3.00

This course is required for MSA and MSF students and it is also a recommended elective for MBA students with a finance concentration. This course develops an understanding of the concepts, tools, and applications of economics at both the micro and macro level. The focus is on how economic analysis influences decision-making in the public and private sectors and how economic tools can enhance managerial effectiveness and organizational efficiency. The economic role of government and its impact on the business environment in a market economy, the factors that influence firm performance and competitiveness, and the role of financial institutions in the current economic environment are discussed throughout the course.

3.00

This course introduces students to the concepts and applications of data analytics on large data sets for managerial decision making. Students will learn foundation skills needed to extract valuable information out of data, including various descriptive and predictive analytics techniques. Students develop knowledge of data visualization and interpretation coupled with conveying data, results and insights. Issues on data acquisition, storage and management will be discussed.

3.00

This course deals with the structure and information content of the three principal financial statements of profit-directed companies, namely the income statement, balance sheet, and statement of cash flows. It develops skill in using accounting information to analyze the performance and financial condition of a company, and to facilitate decision making, planning and budgeting, and performance appraisal in a managerial context. This course also contains an experiential component by offering guided inquiry and real company cases.

1 course from each of the following groups: MBA-615 or SBS-603; MBA-625 or SBS-604; MBA-640 or ACCT-800; These courses may be taken prior to or concurrently with MBA-650.

3.00

This course introduces the basic principles of corporate finance. The main focus is on fundamental principles such as time value of money, asset valuation, and risk and return tradeoff. Topics to be covered also include cost of capital, capital budgeting, and capital structure.

MBA 650

3.00

An in-depth analysis of financial statements, this course is designed to help investors and managers in their assessment of business entity. This course also analyzes financial services industry: bank financial statement analysis with an emphasis on off- balance sheet lending and borrowing, capital structure issues, and innovations in mortgage-backed securities and asset-based financing techniques are covered. Additionally, the tax implications of various derivative securities is studied.

Take MBA 650

3.00

This course extends the body of knowledge acquired in MBA 650. Students expand knowledge of dividend theory, capital structure theory, capital budgeting, long-term financing decisions, cash management and corporate restructuring, market efficiency, and risk and liability management.

MBA-650

3.00

Students examine markets for investment procedures, valuation models, basic analytical techniques, and factors influencing risk/return tradeoffs. This course emphasizes the professional approach to managing investment assets. A variety of investment vehicles are discussed, including stocks, bonds, options, and futures.

MBA-650

3.00

Students explore the pricing of options and futures contracts, the characteristics of the markets in which these contracts are traded, options and futures strategies, and the application of these contracts in the hedging of financial positions. In addition, students are exposed to swap markets and a variety of swaps.

MBA-650

3.00

Students are introduced to mathematical statistics and basic econometrics. They study fundamental econometric tools as well as hypothesis testing, analysis of variance, linear regressions, simultaneous equations, and models of qualitative choice.

3.00

Analyzes various real world business problems and explores the full scope of MS Excel's formulas, functions and features to create data models and present solutions. Students analyze data, design custom charts, graphs, PivotTables and Pivot charts, create three-dimensional workbooks, build links between files and endow worksheets with decision-making capabilities. Students conduct What-If Analysis, utilizing Scenario Manager, Solver, Data Tables and Goal Seek. This course provides the skills necessary to pass the Microsoft Office Specialist Certification in Excel.

This course was formerly ISOM-815

3.00

Introduces the importance of information as an organizational resource, role of big data in organizations, and the application of tools to provide high quality information. Students will be able to select the most appropriate data management tool (e.g., SQL vs. non-SQL databases) to business scenarios. Develops the skills needed to succeed in today's big data environment through the application of data management techniques, cases and exercises. Students will become proficient in designing databases using entity relationship modeling and normalization, in building and querying databases of various sizes with Access and SQL (an industry standard), preparing high quality data and applying data visualizing techniques. Students will complete a series of business-oriented hands-on exercises, prepare cases, and complete projects on database design and big data.

3.00

Provides students with an understanding of the nature of enterprise integration and enterprise software, business process reengineering, the implementation within organizations, and strategies for maximizing benefits from enterprise systems. To manage complex business processes in today's multi-national, wired and wireless world, firms need integrated software packages to manage their global business. Enterprise Resource Planning (ERP) systems are used to support a wide range of business functions for all companies across industries. With ERP systems, business managers are able to make decisions with accurate, consistent, and current data. Intensive lab projects on the SAP ERP System with real life business scenarios are utilized to reinforce understanding of enterprise systems functionality and business process concepts.

3.00

This course teaches students how to build and maintain data warehouses, and how to analyze and use this data as a source for business intelligence and competitive advantage. Students study data mining concepts and the use of analytics tools and methods for producing business knowledge. Topics include extraction, transformation and loading; decision support systems; text, web and data mining models as well as data presentation/visualization including dashboards, scorecards and various charts. Students build a data warehouse and practice the extraction and filtering process used to produce high quality data warehouses. Students will use tools such as MS Excel, SAP Lumira, Tableau and SAP Business Warehouse.

3.00

Predictive analytics make predictions about unknown future events. It is crucial for companies to ask the right questions, perform rigorous analysis, and take actions that will result in the most desirable outcomes. This course develops students' capability in applying the core concepts and techniques of predictive analytics to identify opportunity, recognize patterns, predict outcomes, and recommend optimal actions within the context of organizational decision-making. Topics include: business analytics life cycle, data pre- processing, linear and nonlinear regression, tree-based methods, model assessment and selection, and resampling methods.

3.00

Introduces the fundamental principles of information and big data security. Security vulnerabilities, threats and risks will be analyzed. Common types of computer attacks and counter-attacks will be identified. Security technologies such as biometrics, firewalls, intrusion detection systems and cryptography systems will be applied in conjunction with human based safeguards. Business continuity and disaster recovery planning will be covered. Students will then learn how to design and build a layered security defense combining several of the above controls to address the different challenges to data security. The managerial concerns of security and privacy of information will be stressed including the legal and privacy issues. Best practices for planning and auditing security and privacy will then be covered.

Take MBA-650

3.00

This course provides an integrated framework for analyzing and measuring risk with a computer simulation approach. A common set of computational tools will be applied across several different financial applications ranging from options pricing to portfolio design. Extensive time will be spent on estimating and simulating 'Value at Risk' which has been a standard for measuring risk in large financial institutions. We will also compare this with other traditional methods as well as other modern methods, such as extreme value theory at quantifying risk. Computationally intensive methods, such as bootstrapping, and Monte Carlo analysis will be used extensively throughout the course with MATLAB as the primary programming tool.

Take ISOM-835

3.00

This course is built upon the predictive modeling course and covers a broad collect of data mining and business intelligence techniques, including logistic regression, discriminant analysis, support vector machines, clustering methods, network analysis, association rule mining, text mining, etc. It focuses on turning data into business intelligence and eventually use data and analytics to create business value. The course takes a holistic approach of business analytics, starting from identifying and defining business questions, evaluating data quality, cleaning and preparing data to selecting models, interpreting outcomes, and communicating analysis and results to technical and management audiences. Throughout the course, students are involved in hands-on analysis using large sets of real data from a variety of industries. A term project and a formal presentation of the project are required.

Take FIN-808, FIN-810, and FIN-814. (FIN-814 can be taken concurrently)

3.00

Students examine financial theories, techniques, and models applied to the study of corporate financial decisions, aspects of corporate strategy, industry structure, and the functioning of capital markets.