Master of Science in Information Systems Management (MSISM)
The Master of Science in Information Systems Management's 12-course curriculum prepares you to be a responsible leader in the fast-growing information systems field. The program has one prerequisite: a statistics course (ISSCM 491 or its equivalent)
This course uses database systems as the focus for studying concepts of data modeling and data manipulation. Procedures for creating, managing, sorting, and processing data are discussed. Concepts of relational database methods are covered as well as the issues that arise in managing information in a database and using it to support business processes.
Outcome: Understanding the development and use of business database systems.
This course focuses on how to effectively use a computer programming language to support decision making in business. Examples include using Visual Basic for Applications (VBA) to create applications within Microsoft Excel or using Python for manipulating and analyzing data. In addition to covering the concepts of programming using the specified language, this course covers developing user interfaces, working with external data and debugging code. By the end of this course, the student will be able to build custom procedures and create user-defined functions in the programming language used
This course examines the ethical aspects of individual and corporate decision making in business and provides resources for making ethical decisions within the context of managerial practice.
Outcome: Students will be acquainted with the concepts and principles of ethical reasoning that have been developed in ethical theory; be aware of the specific ethical issues that arise in management and of the ways in which these issues are commonly analyzed; and be able to make sound ethical and managerial decisions and to implement those decisions within the context of an organization in a competitive marketplace.
This is an advanced business ethics course that addresses the ethical issues that arise in the global business environment, including the standards for the operation of multinational corporations and the ethical perspectives of managers in different countries.
Outcome: Students will understand the specific ethical problems of international business and of different ethical perspectives; develop skills for personal decision making and for developing and implementing ethical corporate policies in international business; and learn how to work toward more effective background institutions and forms of international business regulation.
Choose at Least Six (6)
Business analytics is the practice of using methodically collected data to drive decisions about business and in business applications. The goal of the course is to introduce students to the current approaches, tools, and techniques involved in this practice. Because many topics and concepts in business analytics are best learned through hands-on work, time will be spent obtaining, processing, analyzing and visualizing data that pertain to different business cases. Students will use R, arguably the most popular analytical software used by data scientists. During this course, students will learn to use R, as well as gain and help improve business insight through data-driven analytics.
Outcomes: Explain the key factors differentiating business intelligence from business analytics. Frame a problem in a business analytics context to drive insightful decisions and gain the competitive edge.
Scheduled classes are offered on an ad hoc basis. Specific titles, prerequisites and content will vary.
Outcome: Students will be able to demonstrate understanding of specialized topics not otherwise covered by department regular course offerings
Data Mining involves the search for patterns in large quantities of data. The fundamental techniques used in data mining include, but are not limited to, clustering, decision trees, neural networks, and association analysis.
Outcome: The student will be able to build models using an industry-standard package and interpret the results.
Provides a core set of skills for planning, managing and executing systems analysis and design processes in e-business and Web-based environments. Topics typically include project initiation and planning, methods used in the determination of information requirements, prototyping, techniques used in systems design, testing and implementation strategies.
Outcome: Understanding of the development and implementation of business information systems.
This course introduces the student to economic and business practices of a foreign country using the analysis of data, and on-site experiences. We will focus on business strategies, impediments, and challenges in light of the culture, politics, history and institutions of a selected country. We will interact with a variety of local people such as small business owners, firm managers, economists, journalists, and students, in order to inform our understanding and analysis.
Outcome: Students will gain knowledge and analytical skills that can assist them in facing the challenges of conducting business in global locations.
The amount of data that our world generates is growing at a torrid pace. Sifting through & making sense of these humongous mountains of data is crucial to ensuring business growth, success and to making scientific discoveries & advancements. Data visualization plays an important role in this process.
Outcome: Students will be able to process & visualize large amounts of data in order to enable efficient & effective analysis using industry standard software.
The components and design issues related to data warehouses and business intelligence techniques for extracting meaningful information from data warehouses are emphasized. Oracle tools will be used to demonstrate design, implementation, and utilization issues.
Outcome: students will learn how data warehouses are used to help managers successfully gather, analyze, understand and act on information stored in data warehouses.
This course will be based on current best practices in IS development and focus on the importance of quality as an activity applied throughout the entire systems development process.
The course will cover techniques for ensuring quality in systems development such as software defect prevention and removal methods. Examples of how such concepts and techniques are used in firms in different industries will be examined. The following topics will also be discussed: software metrics, quality in software requirements, Function Point Analysis & Metrics, and Quality Management Systems such as Six Sigma, ISO 9000, Capability Maturity Model and Information Technology Infrastructure Library (ITIL).
The art and science of project management as applied to a variety of business and technical projects in commercial, public, and private sectors. Covers: project life cycle and methodology; teambuilding; project organization, stakeholders and leadership; proposals and contracts; techniques for project planning, estimating, scheduling, and control; PMO.
Outcome: Understanding of the broader role of the project manager with regard to all project stakeholders, and of methods, tools, and procedures for initiating, defining, and executing projects.
Techniques of forecasting and model building are introduced. Methods covered are simple and multiple regression, introduction to time series components, exponential smoothing algorithms, and AIRMA models - Box Jenkins techniques. Business cases are demonstrated and solved using the computer.
Outcome: To be able forecast business and economic variables to enhance business decisions.
A study of the design, development, and use of decision models for analysis of supply chain problems. This course provides an example-driven approach to learn about important supply chain models, problems, and solution methodologies. The objectives of this course are to develop valuable modeling skills that students can appreciate and use effectively.
Outcomes: Students will have developed an understanding of the issues involved in the use of decision support tools for analysis of supply chain problems.
Choose up to Three (3)
The purpose of this course is to help students understand feasible econometric techniques in order to mine information to understand economic and financial patterns and to forecast. A rigorous exposition of the theory behind econometric techniques will help students understand the issues raised in different published papers. Topics of econometric techniques covered in this course include panel data analysis, time-series models, discrete choice models, and methods to identify causality between variables. Practical applications will prepare students to use these methods in their own projects.
This course is designed as an introductory graduate level course in analytical problem solving, another name for research methods, and design. A basic understanding of - and general familiarity with fundamentals of statistical concepts is assumed. However, where necessary, we will revisit these concepts briefly. Of course, this is not a course in statistics.
This course develops an understanding of the marketing research process and the role of survey research in it.
Outcome: Students formulate research problems and a design research study, including the development of a questionnaire, selection of an appropriate sample and data analysis.
Prerequisites: MARK 460.
This course develops an understanding of the development and use of databases for marketing, retrieval of appropriate data and analysis of that data to increase marketing effectiveness.
Outcome: The student will perform database manipulation and analysis of data. Analysis includes at least univariate analysis, cross-tabulation, creation of new variables, regression analysis and recency-frequency-monetary analysis.
In this course the students will study how to use data analytics to learn about customer needs and improve targeting individual consumers. The course will encourage students to apply scientific methods and models to predict and respond to customer choices. This is the key part of learning Big Data. The term Big Data is viewed in the broad sense as it relates to various aspects of the consumer behavior, which may be captured, measured, and transformed to the digital form.
Through applications of statistical models to the analysis of the real-world databases, the students will learn how firms may use customer data to serve customers better.
This course is designed with marketing managers in mind. As profession marketing is evolving, it is no longer based primarily on the conceptual content. Marketers get exposed to thousand times the volume of data she(he) saw five years ago. More data cannot lead to better decision making unless managers learn how to use that data in meaningful ways. In this course, the students will be introduced to the analytical decision models that assist modern managers in making marketing decisions related to the targeting, product design, communications, etc.
Learning Outcomes: The objectives of this course are the following: 1. To learn analytical techniques and decision models for enhancing marketing decision making in the modern organizations 2. Improve skills to viewing marketing processes and relationships systematically and analytically 3. To learn power of decision models applied in the real managerial contexts 4. To provide students with toolkit that may be used to assess and measure return on marketing investments in organizations
This course examines how business partners along the supply chain can work together to gain competitive advantage in moving products and services around the world to satisfy customers.
Outcome: Understanding best practices like vendor-managed inventory and category management, and the application of information technologies for sharing information.
Loyola's Quinlan School of Business invites you to join us at our downtown Chicago Water Tower campus for an Open House or Information Session. Please contact us with any questions about our information systems management courses.