Business Analytics (M.S.)
The Gabelli School Master of Science in Business Analytics (MSBA) will help you to see the big picture that your future employer is going to ask you to draw. The curriculum teaches you to pull valuable conclusions from a wide range of information types: big data, business performance data, web and text content, and more.
The Gabelli School MSBA provides skills in:
- Artificial intelligence and deep learning
- Business analytics
- Data engineering
- DevOps engineering for data science
- Programming for analytics and data science
- Statistical analytics for business
The MSBA has two schedule choices; a one-year full-time program or a part-time program spread over a longer time frame, such as two years—ideal for professionals who don’t want to leave their jobs while they pursue the degree.
To learn more about the M.S. in Business Analytics, visit the Fordham website.
CIP Code
30.7102 - Business Analytics.
You can use the CIP code to learn more about career paths associated with this field of study and, for international students, possible post-graduation visa extensions. Learn more about CIP codes and other information resources.
The 30-credit program consists of 10 courses (seven required and three electives), across three semesters. Students can earn the MSBA in one year of full-time study or two years of part-time study. The schedule below outlines the full-time format; part-time students coordinate their coursework with guidance from the program director and academic adviser.
Through the selection of elective courses, the program allows students to specialize in one of four career-oriented tracks, according to their interests. They can choose from tracks in:
- Artificial Intelligence and Deep Learning
- Business Analytics
- Programming for Analytics and Data Science
- Statistical Analytics for Business
For details on MSBA tracks, see the Tracks tab.
| Fall | Credits | |
|---|---|---|
| BYGB 7973 | Database Management | 3 |
| BYGB 7978 | Web Analytics | 3 |
| BYGB 7967 | Data Mining for Business | 3 |
| One elective course (see options below) | 3 | |
| Credits | 12 | |
| Spring | ||
| BYGB 7975 | Bus Analytics for Managers | 3 |
| BYGB 7977 | Text Analytics | 3 |
| BYGB 7990 | Big Data Analytics | 3 |
| One elective course (see options below) | 3 | |
| Credits | 12 | |
| Summer | ||
| BYGB 7988 | Bus Perf Mgmt Risk Analytics | 3 |
| One elective course (see options below) | 3 | |
| Credits | 6 | |
| Total Credits | 30 | |
Electives
Courses in this group have the BUAN attribute.
| Course | Title | Credits |
|---|---|---|
| ACGB 719G | Audit Data Analytics | 3 |
| ACGB 719H | IT Audit and Information Assurance | 3 |
| BEGB 6220 | Econ Analysis & Bus Decisions | 3 |
| DGGB 6820 | Statistics | 3 |
| DGGB 7844 | Stat Methods and Comp I | 3 |
| FNGB 74BG | Auto Trading Systems - Intro | 3 |
| GFGB 6005 | Financial Modeling | 3 |
| ISGB 6910 | Business Tech & Analytics | 3 |
| ISGB 7902 | System Analysis & Design | 3 |
| ISGB 7910 | Info Systems Strategy & Mgmt | 3 |
| ISGB 7922 | Healthcare IT | 3 |
| ISGB 7924 | Mobile E-Commerce and Apps | 3 |
| ISGB 7932 | Accounting Info System | 3 |
| ISGB 7933 | Audit Data Analytics | 3 |
| ISGB 7934 | Artificial Intelligence | 3 |
| ISGB 7942 | Optimization Models in Bus | 3 |
| ISGB 7943 | Programming with Python | 3 |
| ISGB 7944 | Sports Analytics | 3 |
| ISGB 7955 | Project Management | 3 |
| ISGB 7980 | Bus Modeling w/Adv Sprdsheets | 3 |
| ISGB 7985 | Data Warehousing | 3 |
| ISGB 799D | Cybersecurity for Business | 3 |
| ISGB 799R | IT Audit and Information Assurance | 3 |
| ISGB 799V | R Statistical Programming | 3 |
| ISGB 799X | Fintech -An Introduction | 3 |
| ISGB 799Y | Blockchain Tech & App Dev | 3 |
| ISGB 799Z | Deep Learning | 3 |
| ISGB 79AA | Advanced Python for Financial Programming | 3 |
| ISGB 79AC | Cybersecurity Analytics for Business | 3 |
| ISGB 79AD | Digital Forensics | 3 |
| ISGB 79AE | Robotic Process Automation | 3 |
| MKGB 7730 | Research Methods | 3 |
| MKGB 779I | Data-Driven Marketing Decisions | 3 |
| MKGB 77AA | Marketing Decision Models | 3 |
| MKGB 879X | Applied CRM | 1.5 |
| OPGB 6627 | Operations and Supply Chain Management | 3 |
| QFGB 8911 | Financial Markets and Modeling | 2 |
| QFGB 8923 | Machine Learn & Econometrics | 2 |
| QFGB 8925 | Simulation Applications | 2 |
| QFGB 8943 | Large-Scale Data Modeling | 2 |
| QFGB 8955 | Computational Finance | 2 |
| QFGB 8968 | Blockchain Technology and Application Development | 3 |
| SDGB 7840 | Applied Regression Analysis | 3 |
| SDGB 7841 | Statistical Theory I | 3 |
| SDGB 7842 | Statistical Theory II | 3 |
| SDGB 7843 | Judgment and Decision Making | 3 |
| SDGB 7844 | Stat Methods and Comp I | 3 |
| SDGB 7847 | Machine Learning for Stats | 3 |
| SDGB 7848 | Observational Studies | 3 |
| SDGB 7851 | Measurement and Data Visualization | 3 |
Students seeking special permission to count a course without the BYGB or ISGB subject code as an elective must follow the below, three-step approval process.
Only 6000-level or above courses may be considered for electives to count towards the MSBA.
- The student should send a detailed petition to the MSBA Program Director explaining why they are considering a non-BYGB or ISGB subject code course as an elective.
- The student should request permission from the instructor of the relevant course to join the elective, who should then send an email to the student authorizing the student's enrollment in the course. The student should forward that email to the MSBA Program Director and MSBA Advising Dean.
- The MSBA Program Director and MSBA Advising Dean will discuss the request, giving it due consideration, and render a decision on whether the non-BYGB or ISGB subject code course may be accepted as an elective.
Note: all advanced ISGB courses with prerequisites must be met (please discuss with the Program Director/Advising Dean).
For students who are not interested in any of the below tracks, another option is to create an optimal mix of electives across the tracks, in consultation with the program director and area chair.
Artificial Intelligence and Deep Learning Track
Courses in this group have the BUAI attribute.
| Course | Title | Credits |
|---|---|---|
| ISGB 7934 | Artificial Intelligence | 3 |
| ISGB 799Z | Deep Learning | 3 |
| ISGB 79AA | Advanced Python for Financial Programming | 3 |
| ISGB 79AE | Robotic Process Automation | 3 |
Business Analytics Track
This track is for students interested in specializing in the analytics and data science aspects of information technology. Courses in this group have the BUBA attribute.
| Course | Title | Credits |
|---|---|---|
| ISGB 6910 | Business Tech & Analytics | 3 |
| ISGB 7933 | Audit Data Analytics | 3 |
| ISGB 7942 | Optimization Models in Bus | 3 |
| ISGB 7944 | Sports Analytics | 3 |
| ISGB 7980 | Bus Modeling w/Adv Sprdsheets | 3 |
| ISGB 7985 | Data Warehousing | 3 |
| ISGB 799R | IT Audit and Information Assurance | 3 |
| ISGB 79AC | Cybersecurity Analytics for Business | 3 |
| ISGB 79AD | Digital Forensics | 3 |
Programming for Analytics and Data Science Track
This track is for students who wish to delve deeper into the development of analytics and data science applications. Courses in this group have the BUDS attribute.
| Course | Title | Credits |
|---|---|---|
| ISGB 7943 | Programming with Python | 3 |
| ISGB 799V | R Statistical Programming | 3 |
| ISGB 799X | Fintech -An Introduction | 3 |
| ISGB 799Y | Blockchain Tech & App Dev | 3 |
| ISGB 79AA | Advanced Python for Financial Programming | 3 |
| ISGB 79AE | Robotic Process Automation | 3 |
Statistical Analytics for Business Track
Courses in this group have the BUSA attribute.
| Course | Title | Credits |
|---|---|---|
| ISGB 799V | R Statistical Programming | 3 |
| SDGB 7840 | Applied Regression Analysis | 3 |
| SDGB 7841 | Statistical Theory I | 3 |
| SDGB 7842 | Statistical Theory II | 3 |
| SDGB 7843 | Judgment and Decision Making | 3 |
| SDGB 7844 | Stat Methods and Comp I | 3 |
| SDGB 7851 | Measurement and Data Visualization | 3 |