Master of Science in Applied Business Analytics
With the accelerating evolution of technology and mobile applications, it is ever more critical for leaders to acquire the skills to assess the burgeoning amounts of data captured. According to a 2016 report by the McKinsey Global Institute, the volume of data doubles every three years. As data-driven business models change the face of industry, developing the ability to capitalize upon this valuable resource is compulsory. In fact, PwC predicts 2.7 million job postings for data science and analytics roles by 2020. PwC also notes that 67 percent of data analytics posts are for analytics-enabled leadership roles such as chief executive officer, chief data officer, director of IT, human resources manager, financial manager, and marketing manager.
With its unique combination of dynamic academic curriculum, the latest educational technologies, flexible delivery modes, advanced pedagogy, and professional contacts within the business analytics industry, Metropolitan College’s Master of Science in Applied Business Analytics (MSABA) provides comprehensive coverage of the state-of-the-art concepts, techniques, and tools used in the process of data-driven business decision-making. Whether studying online or on campus, students gain hands-on experience with a variety of analytical models and decision-support tools, and to apply them to interlinked data-inputs and large data sets in the areas of marketing, operations, product and technology innovations, financial services, and others. The curriculum covers advanced software tools and functions such as descriptive, predictive, and prescriptive modeling; text and data mining; visual analytics; and business simulations. Graduates of the program will be able to analyze data-driven business processes, select appropriate analytical methods to monitor and identify performance issues, prescribe possible outcomes, and propose optimal data-based solutions.
Students who complete the master’s degree in Applied Business Analytics will be able to demonstrate:
- The knowledge and skills to better utilize available information in operational, tactical, and strategic decision-making in organizations.
- Experience with various powerful emerging technologies and techniques for increasing the value of both in-house and third-party data sets.
- An understanding of how organizations are using interlinked data-inputs, analytics models, and decision-support tools to better understand their operations, customers, and markets.
- Expertise in web analytics and metrics, and the ability to procure and process unstructured text, and delve into hidden patterns within data sets.
- The ability to facilitate knowledge discovery using data-mining and visualization techniques over vast amounts of data.
MS in Applied Business Analytics Program Options
Available on campus and in the following format:
MET prioritizes the review and admission of applications submitted earlier in the rolling admission process. You are encouraged to submit your application as soon as possible and no later than the priority application deadlines for each term.
Applicants must have an earned bachelor’s degree, in any field of study, from a regionally accredited college/university (or the international equivalent) prior to enrollment at Metropolitan College. The following materials are required for a complete application:
- Completed Application for Graduate Admission and application fee
- All college transcripts
- Personal statement
- Three letters of recommendation
- Official English proficiency exam results (International students)
Transfer of Credits
A maximum of two graduate-level courses (8 credits), completed with a grade of B+ or better and not used toward another degree, may be transferred from an accredited university with approval from the Administrative Sciences department. The courses must have been completed no more than two years prior to matriculation. To request transfer of credits, students must fill out a transfer of credit form and attach all pertinent information.
Part-time students who hold a bachelor’s degree, but have not yet applied as degree candidates, may enroll in a maximum of two courses on a space-available basis. Before registering in any of our graduate courses (600 level or higher) you will need to provide the department with an undergraduate transcript confirming your degree from an accredited university. Please note that only two courses taken prior to acceptance into the program will be counted toward the degree.
Students accepted into the program who have already earned the Graduate Certificate in Applied Business Analytics at MET have satisfied the specialization requirements of the MSABA and need only complete the Degree Core Courses and two electives to earn the master’s degree.
No grade lower than B– may be applied toward degree, certificate, or diploma requirements. Students with less than a 3.0 cumulative GPA will be placed on academic probation. Students on academic probation must make satisfactory progress toward achieving a minimum of 3.0 by the following semester, and must be in a position to graduate with a 3.0 or better within the remaining program courses. While grades of B or B– are normally considered passing, these grades will not assist in raising an unsatisfactory GPA to a satisfactory level. Therefore, students must obtain a minimum grade of B+ during a probation period.
Students who, in the determination of the department and based on past academic performance, are not in a position to raise their GPA to the necessary level to graduate within the remaining courses will be dismissed from the program. Students who have not removed themselves from academic probation after one semester for full-time status (three semesters for part-time status) will be dismissed from the program.
As a prerequisite to the course MET AD 571 Business Analytics Foundations, students are required to complete the AD 100 Pre-Analytics Laboratory (online). Some courses may have additional prerequisites. Please note that MET AD 571 is a prerequisite for all four specialization courses and should be taken early in the degree.
A total of 40 credits is required.
All students must satisfy the degree core courses, specialization courses, and electives as indicated. Waived courses from must be replaced by an elective course in order to meet the 40-credit-hour requirement.
Degree Core Courses
(Four courses/16 credits)
MET AD 571 Business Analytics Foundations
Prereq: AD100 Pre-Analytics Laboratory
This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidation, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). Students will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data-inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. [ 4 cr. ]
|A1||IND||Youssef||CAS 326||M||2:30 pm – 5:15 pm|
|A4||IND||Staff||KCB 106||W||2:30 pm – 5:15 pm|
|A6||IND||Ritt||KCB 103||W||6:00 pm – 8:45 pm|
MET AD 605 Operations Management: Business Process Fundamentals
This course helps students to develop an understanding of the impact of business processes on the organization's performance and provides students the key tools to analyze and improve processes in both manufacturing and service sectors. [ 4 cr. ]Fall 2020
|A1||IND||Maleyeff||CGS 527||M||2:30 pm – 5:15 pm|
|A3||IND||Cashton||CAS 235||T||6:00 pm – 8:45 pm|
|A4||IND||Maleyeff||CAS 233||W||6:00 pm – 8:45 pm|
|A5||IND||Maleyeff||MET 122||R||12:30 pm – 3:15 pm|
MET AD 632 Financial Concepts
Introduction to the concepts, methods and problems of accounting and financial analysis. Includes accounting principles, measurement and disclosure issues, financial statement analysis, time value of money, cash flow projection and analysis, capital budgeting and project evaluation, bond and equity valuation, cost of capital and capital structure. 4 cr. [ 4 cr. ]Fall 2020
|A1||IND||Becker||SHA 210||M||6:00 pm – 8:45 pm|
|A2||IND||Mcgue||KCB 104||T||12:30 pm – 3:15 pm|
|A3||IND||Mendlinger||CAS 233||T||6:00 pm – 8:45 pm|
|A5||IND||Mcgue||MCS B31||R||12:30 pm – 3:15 pm|
|A6||IND||Mcgue||SHA 210||R||6:00 pm – 8:45 pm|
MET AD 715 Quantitative and Qualitative Decision-Making
Explores decision making and policy formulation in organizations. Includes goal setting and the planning process, rational models of decision making, evaluation of alternatives, prediction of outcomes, cost-benefit analysis, decision trees, uncertainty and risk assessment, and procedures for evaluation of outcomes. [ 4 cr. ]Fall 2020
|A1||IND||Staff||MCS B31||T||12:30 pm – 3:15 pm|
|A2||IND||Youssef||CAS 326||T||6:00 pm – 8:45 pm|
|A3||IND||Zlatev||CAS 237||W||2:30 pm – 5:15 pm|
|A5||IND||Youssef||KCB 107||R||12:30 pm – 3:15 pm|
(Four courses/16 credits)
MET AD 616 Enterprise Risk Analytics
The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data-inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. [ 4 cr. ]
|A1||IND||Ritt||CAS 233||M||6:00 pm – 8:45 pm|
|A2||IND||Doddavaram||MET 122||T||12:30 pm – 3:15 pm|
MET AD 654 Marketing Analytics
Become familiar with the foundations of modern marketing analytics and develop your ability to select, apply, and interpret readily available data on customer purchase behavior, new customer acquisition, current customer retention, and marketing mix optimization. This course explores approaches and techniques to support the managerial decision-making process and skills in using state-of-the-art statistical and analytics tools. Students will have an opportunity to gain basic understanding of how transaction and descriptive data are used to construct customer segmentation schemas, build and calibrate predictive models, and quantify the incremental impact of specific marketing actions. [ 4 cr. ]
|A1||IND||Youssef||CAS 426||W||6:00 pm – 8:45 pm|
|A2||IND||Page||CAS 213||W||2:30 pm – 5:15 pm|
MET AD 688 Web Analytics for Business
Explore web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of websites, their content, user behavior, and reporting. The Google analytics tool is used for collection of website data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module presents how web crawlers process and index the content of web sites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. [ 4 cr. ]
|A1||IND||Harris||CAS 315||M||6:00 pm – 8:45 pm|
|A2||IND||Doddavaram||CAS 213||T||6:00 pm – 8:45 pm|
MET AD 699 Data Mining for Business Analytics
Enterprises, organizations and individuals are creating, collecting, and using massive amount of structured and unstructured data with the goal to convert the information into knowledge, to improve the quality and the efficiency of their decision-making process, and to better position themselves to the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of the business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal to understand (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. [ 4 cr. ]Fall 2020
|A1||IND||Page||CAS 315||T||6:00 pm – 8:45 pm|
|A2||IND||Page||SOC B57||T||12:30 pm – 3:15 pm|
(Two courses/8 credits)
Choose two additional Metropolitan College graduate courses, with the approval of an advisor, to enhance your individual management interests or to work toward a certificate.
Second Master's Degree Option
In appreciation of the converging nature of management skills and technology, the Administrative Sciences department collaborates with Metropolitan College’s departments of Actuarial Science and Computer Science. Degree candidates in either program may apply 8 credits from one degree toward a second degree in one of these disciplines, thereby reducing their work by two courses.
Interested students may apply for a second master’s degree program only after enrollment at MET. Students who apply for a second master’s degree are eligible to waive the application fee and may also request that their application materials (including references and transcripts) be forwarded from the first application to the second. Upon acceptance to the second master’s degree, credit transfer may be applied for up to 8 credits.
View all Administrative Sciences graduate courses.