Survival in today's marketplace demands professionals who combine a passion for innovation with the ability to analyze and interpret large volumes of data.
But few managers possess the technical training to successfully lead their organization's forays into technologies such as Twitter, Facebook and the Internet of Things. That leaves those companies unable to capitalize on the limitless opportunities available through such universally available tools and the endless data they provide.
The Business Intelligence & Analytics Master's Degree program provides the analytical and professional skills necessary to take advantage of this data, to move organizations from the traditional mode of intuition-based decision-making to fact-based decision-making.
The curriculum covers the concepts and tools at the forefront of the Big Data revolution: database management, data warehousing, data and text mining, social network analytics, optimization, risk analytics, and technologies such as Hadoop and data stream analytics. Upon earning their degrees, students will have completed a capstone course requiring them to work on a major project, using real data, under the guidance of an industry mentor. Coursework also emphasizes training in traditional business skills, such as oral and written communication skills, analytical thinking, and ethical reasoning.
Going beyond the data
The Business Intelligence & Analytics program emphasizes the application of Big Data to business problems, ensuring graduates can build actionable strategies based on the numbers.
Who Should Apply
The master's in Business Intelligence & Analytics was created to connect quantitatively oriented students with industry, to prepare them to bring a blend of management and analytical skills to companies in financial services, life sciences, retail, media and beyond. The curriculum is designed to build upon the kind of undergraduate work students are exposed to in pursuing undergraduate degrees in science, mathematics, computer science and engineering. The program is available to students who wish to pursue this degree full- or part-time.
Admission to this program is highly selective, and at least one year of work experience is preferred in order to keep classroom discussing moving at a brisk pace. However, applicants are not required to have experience and can enroll in the program immediately after completing a bachelor's degree.
To be considered, students must include the following with their applications:
- Two letters of recommendation.
- Official transcript from each academic institution attended.
- Official conferment of your bachelor’s degree, with a B average, in science, mathematics, computer science, engineering or a related field.
- One year of calculus.
- Once course covering basic probability, hypothesis testing, and estimation.
- An up-to-date résumé.
- Competitive GMAT or GRE score.
- Competitive TOEFL score (international students only).
Its unique location just across from Manhattan supports the Stevens master's in Business Intelligence & Analytics by putting the campus within easy reach of many Fortune 500 companies — most of whom have an insatiable thirst for data scientists and managers who combine business and analytical skills. Recruiters frequent the Stevens campus to meet the best and brightest students, while managers deliver guest lectures or suggest consulting work for students and faculty researchers. The university's location is felt strongest in a required practicum course in which students work on a major project, using real data, under the guidance of an industry mentor at a nearby company.
The master's program is structured to train students who understand both the business implications of Big Data and the technology that makes that data useful. The curriculum develops students' professional skills, disciplinary knowledge, and technical abilities, leaning heavily on the high-tech infrastructure at Stevens to give students direct exposure to the kind of challenges they will engage in the workplace. Students will cultivate the skills to collect, analyze and interpret data in strategic data planning and management; databases and data warehousing; data mining and machine learning; network analysis and social media; and risk, modeling, and optimization, and will learn to apply those skills to business problems in order to form actionable strategy.
|Organizational context||FIN 615 Financial Decision Making||-|
|Database||MIS 630 Data and Knowledge Management||MIS 636 Data Warehousing and Business Intelligence|
|Optimization and risk||BIA 650 Optimization and Process Analytics||BIA 670 Risk Management: Methods & Applications|
|Statistics||BIA 652 Multivariate Data Analytics||BIA 654 Experimental Design|
|Data Mining||MIS 637 Knowledge Discovery in Databases||BIA 656 Statistical Learning & Analytics *|
|Social Networks||BIA 658 Social Network Analytics||BIA 660 Web Mining *|
|Management Applications||BIA 672 Marketing Analytics *||BIA 674 Supply Chain Analytics *|
|Big Data Technologies||BIA 676 Data Stream Analytics: Internet of Things *||BIA 678 Big Data Seminar *|
|Practicum||BIA 686 Applied Analytics in a World of Big Data||BIA 702 Curriculum Practical Training **|
The master's program includes a concentration tailored to the career demands of students in data science.
This highly flexible concentration prepares students to become specialists in the highly in-demand field of data science. Working with their advisor, students select between two and four courses offered in the Computer Science, Financial Engineering and Mathematics departments at Stevens.
This school offers programs in:
Last updated February 8, 2018