About our Program
The AACSB accredited Rutgers School of Business in Camden, NJ is pleased to announce a Master of Science in Business Analytics (MSBA) program. This is a fully online, 30-credit graduate degree program that can be completed on either a full-time (12 months) or part-time basis.
Our program is designed with working professionals in mind, allowing you to complete the degree on your own schedule and at your own pace. We also offer the opportunity to earn a 12-credit certificate in Business Analytics.
The rapid growth of technology has generated increasing amounts of data, which has led to strong demand for analytics skills. Organizations are seeking individuals capable of gathering, cleaning, mining, modeling, and visualizing business data in order to gain insight into business processes, improve productivity, detect problem areas, identify opportunities, and boost profitability. Business data can be mined to predict customer purchase or churn, detect fraudulent behavior, analyze flow and traffic patterns, etc. in a variety of industries, including: high technology, not-for-profit, medical, pharmaceutical, manufacturing, retail, credit, banking, gaming, hospitality, real estate, utilities, trucking, and transportation.
A Master of Science in Business analytics combines the skills of statistics with domain-specific knowledge of various business domains to create a graduate capable of strategizing ways that analytics can be deployed in an organization to help it achieve its key performance objectives. An MSBA can lead to career paths as data analysts, data scientists, business intelligence analysts, digital marketing managers, and data consultants, among others.
The MSBA is comprised of ten courses, through which students acquire knowledge of statistics, machine learning techniques, and relevant software (e.g., SQL, Excel, R, Python etc.) with direct applications to business domains such as marketing, operations, finance, and accounting. With this degree, candidates will learn how to extract, collect, clean, describe, segment, and model data, as well as validate models and clearly communicate the results to stakeholders, while appreciating legal, ethical and strategic issues involved.
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