Master of Science in Business Analytics

Why Choose a Master of Science in Business Analytics Program at UC Online?

The University of Cincinnati Online’s Master of Science in Business Analytics program is nationally recognized and has a proven track record with placing students at successful, high-profile companies. Predictive Analytics Today named UC as the No.1 MS Data Science school in the country and Quacquarelli Symonds (QS) ranked us 18th globally and 7th nationally among U.S. public universities.

The Master’s of Science in Business Analytics online program at UC provides students with expertise in descriptive, predictive, and prescriptive analytics. Many of our graduates are working as data scientists and business analysts at world-leading companies from larger corporations, to startups across the nation.

Note: The MS-Business Analytics program is recognized as a STEM (Science, Technology, Engineering, and Mathematics) program.  According to the National Science Teachers Association (NSTA), “A common definition of STEM education […] is an interdisciplinary approach to learning where rigorous academic concepts are coupled with real-world lessons as students apply science, technology, engineering, and mathematics in contexts that make connections between school, community, work, and the global enterprise enabling the development of STEM literacy and with it the ability to compete in the new economy.”  UC Online’s skilled faculty members bring valuable field experiences to their courses to ensure that students have the skills necessary to excel in STEM positions.

What is Business Analytics?

According to U.S. News, Business Analytics Business “is the science of using data to build mathematical models and arrive at decisions that have value for a company or organization, Bertsimas says. This is relevant in nearly every field, whether it’s medicine, technology, retail or real estate”.

The University of Cincinnati’s online Business Analytics Master’s program is designed to achieve several core objectives:

• Put you ahead of the competition when applying to the workforce
• Provide you with the skills and tools needed to collect data and analyze it to influence decisions in an organization
• University of Cincinnati’s 100% online program will empower you with core business analytics skills, and technical skills for understanding and implementing descriptive, predictive, and prescriptive analytics

Accreditation

The University of Cincinnati Carl H. Lindner College of Business has proudly been AACSB Accredited since 1919.

UC Online’s Master’s in Business Analytics program offers you:

• A 100% online Bootcamp that prepares you before the program begins
• The ability to customize your degree around your busy lifestyle
• 100% Online coursework
• One of the most affordable tuition rates in the country
• World-class faculty who provide personalized attention to each and every student
• An immersive experience where you’ll gain an understanding of the tools and techniques needed to turn descriptive, predictive, and prescriptive analytics data into meaningful business insights.
• Start-to-Graduation Support: Every student enrolled online is assigned a dedicated Academic Advisor and also a Student Success Coordinator providing one-on-one support. They are your on-campus partners who can help you manage your time and ensure you’re meeting degree requirements to get you to graduation.

Learning Outcomes Based on Career Goals

• Business Analytics: Understand the tasks and techniques needed to recognize business needs and determine solutions to business problems. Software-systems based solutions will drive efficiencies in identifying gaps.
• Data Science: Gain expert knowledge in math and statistics to recognize business needs and analyze data to then apply machine learning and utilize artificial intelligence systems to generate tangible insights for business
• Data Visualization: Gain a deeper knowledge of understanding data visualization tools to provide an accessible way to see and understand trends, outliers, and patterns in data.