Online Master of Science in Applied Business Analytics Degree
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 a recent analysis, PwC determined that 67 percent of job openings requiring data science and analytics competencies are for “analytics-enabled” roles, such as chief executive officer, chief data officer, director of IT, human resources manager, financial manager, and marketing manager. While the jobs are there, there is a shortage of analytics-enabled personnel who combine expertise in their industry with the ability to understand and leverage big data to engage in predictive analytics or make data-informed business decisions.
To help close this skills gap, Boston University’s Metropolitan College offers an online Master of Science in Applied Business Analytics Management degree program. Students have the opportunity to gain hands-on experience with a variety of analytical models and decision-support tools, which they can apply to interlinked data-inputs and large data sets in the areas of marketing, operations, product and technology innovations, financial services, and others. Boston University’s applied business analytics 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 necessary 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.
Awards & Accreditations
Accredited member of AACSB International―The Association to Advance Collegiate Schools of Business
Why Choose BU’s Master of Science in Applied Business Analytics?
- The Applied Business Analytics program offers the flexibility of online or on-campus study formats, ensuring that students can earn their degree the way that suits them the best.
- In 2018, Metropolitan College’s online master’s degrees in management were ranked #9 among the Best Online Graduate Business Programs (Excluding MBA) by U.S. News & World Report.
- Boston University is an accredited member of AACSB International―The Association to Advance Collegiate Schools of Business.
- Learning from expert faculty from MET’s Department of Administrative Sciences, students benefit from our unique combination of dynamic academic curriculum, the latest educational technologies, flexible delivery modes, advanced pedagogy, and professional contacts within the business analytics industry.
14% increase in jobs through 2026
$82,450 median annual pay in 2017
11% increase in jobs through 2026
$84,300 median annual pay in 2017
Market Research Analysts
23% increase in jobs through 2026
$63,230 median annual pay in 2017
Mathematicians and Statisticians
33% increase in jobs through 2026
$84,760 median annual pay in 2017
Operations Research Analysts
27% increase in jobs through 2026
$81,390 median annual pay in 2017
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2017-18 Edition
By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
McKinsey & Company
Big data: The Next Frontier for Innovation, Competition, and Productivity, 2011
By 2020, it is predicted that there will be 2.7 million job postings for data science and analytics roles.
What’s next for the 2017 data science and analytics job market?
Boston University Metropolitan College (MET) offers competitive tuition rates that meet the needs of part-time students seeking an affordable education. These rates are substantially lower than those of the traditional, full-time residential programs yet provide access to the same high-quality BU education. To learn more about current tuition rates, visit the MET website.
Comprehensive financial assistance services are available at MET, including graduate assistantships (up to $4,200 per semester), scholarships, graduate loans, and payment plans. There is no cost to apply for financial assistance, and you may qualify for a student loan regardless of your income. Learn more.
The online Master of Science in Applied Business Analytics consists of 10 required courses (40 credits).*
Students who already hold the Graduate Certificate in Applied Business Analytics may waive the four specialization courses.
*Degree requirements may vary for those students transferring credits from previous coursework at Boston University or receiving course waivers due to professional designations.
Students must complete the degree core courses, specialization courses, and electives as indicated.
As a prerequisite to the course MET AD 571 Business Analytics Foundations, students are required to complete MET AD 100 Pre-Analytics Laboratory. Some courses may have additional prerequisites.
Degree Core Courses
(Four courses/16 credits)
METAD571 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 credits]
METAD605 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 credits]
METAD632 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 credits]
METAD715 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 credits]
(Four courses/16 credits)
METAD616 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 credits]
METAD654 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 credits]
METAD688 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 credits]
METAD699 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 credits]
(Two courses/8 credits)
Choose two additional Administrative Sciences graduate-level courses, with the advice of the Administrative Sciences department coordinator.
The following courses offered by other Metropolitan College departments are allowed with advisor approval:
This course is designed to help students understand and apply the nature of computer crime in the criminal justice field. Several theories (both micro-level and macro-level) will be presented and will be analyzed in depth and applied to computer crime cases both past and present. Students will see how major theories have been re-developed to be applied to computer crime, and by using these theories, students will both develop and explore different strategies for future law enforcement. Students will be presented with common types of fraudulent schemes, as well as several laws that have been enacted and developed specifically for computer crime. In addition, causes, victimization, legal issues, control strategies, and societal costs regarding the "computer-crime" problem will be explored and evaluated. [4 credits]
This course will include a general introduction to the overt as well as underlying ideology, history, reasons and causes of terrorism. Both domestic and international terrorism will be discussed. Domestic hate groups will also receive particular attention. The roles of politics and the media will be discussed. Students will be exposed to the philosophies of terrorists and terrorism. Counter terrorism will also be discussed at length. Students are expected to participate actively in the course. There will be written assignments, a midterm, a class presentation, and a final paper. [4 credits]
METCS634 Agile Software Development
This course provides students with a comprehensive overview of the principles, processes, and practices of agile software development. Students learn techniques for initiating, planning and executing on software development projects using agile methodologies. Students will obtain practical knowledge of agile development frameworks and be able to distinguish between agile and traditional project management methodologies. Students will learn how to apply agile tools and techniques in the software development lifecycle from project ideation to deployment, including establishing an agile team environment, roles and responsibilities, communication and reporting methods, and embracing change. We also leverage the guidelines outlined by the Project Management Institute for agile project development as a framework in this course. [4 credits]
METCS684 IT Security Policies and Procedures
This course enables IT professional leaders to identify emerging security risks and implement highly secure networks to support organizational goals. Discussion of methodologies for identifying, quantifying, mitigating and controlling risks. Students implement a comprehensive IT risk management plans (RMP) that identify alternate sites for processing mission-critical applications, and techniques to recover infrastructure, systems, networks, data and user access. The course also discusses related topics such as: disaster recovery, handling information security; protection of property, personnel and facilities; protection of sensitive and classified information, privacy issues, and criminal terrorist and hostile activities. [4 credits]
METCS688 Web Analytics and Mining
The Web Analytics and Mining course covers the areas of web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of web sites, their content, user behavior, and reporting. Google analytics tool is used for collection of web site 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 studies 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. Laboratory Course. Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. [4 credits]
Associate Professor of the Practice of Administrative Sciences
PhD, MS, BS, Dresden University of Technology
Canan Gunes Corlu
Assistant Professor, Administrative Sciences; Coordinator, Supply Chain Management
PhD, MS, Tepper School of Business at Carnegie Mellon University; BS, Koc University
Associate Professor of the Practice, Administrative Sciences; Coordinator, Enterprise Risk Management
PhD, MS, University of Massachusetts at Amherst
BA, East Stroudsburg State College
M.B.A. Massachusetts Institute of Technology
M.Ed. Harvard University
B.A. Stanford University
Assistant Professor, Administrative Sciences; Coordinator for Global Marketing Management
PhD, State University of New York at Binghamton; MA, Oregon State University; BS, Yonsei University
Associate Professor, Computer Science and Administrative Sciences; Director, Project Management
PhD, University of Manitoba; MS, Florida Institute of Technology; MBA, Webber College; BS, University of Madras, India; PMP (Project Management Professional), Project Management Institute
PhD, MS, Northeastern University; BS, Middle East Technical University
MBA, MS, Northeastern University; BA, University of Massachusetts, Amherst
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