Zicklin's specialized Master's in Business Analytics (MSBA) equips business professionals with the tools necessary to manage data ethically for business success. Students will become expert data analysts who can explore patterns, reveal trends, uncover relationships, and transform data into a catalyst for business growth. More critically, they will also gain the knowledge needed to initiate and evaluate projects that harness this deluge of data.
The MSBA opens the door to exciting new careers in the fast-growing fields of data science and business analytics. The degree is designed for students who are analytically capable and have taken at least one statistics course at the college level in the last five years. The program introduces students to core concepts in Business Analytics with a set of required courses. Students then have the flexibility to specialize in one of the two tracks – data analytics or marketing analytics.
MS in Business Analytics Program Learning Goals
| Data Management | Students will be able to apply methods, tools, and software for acquiring, managing/storing, and accessing structured and unstructured data. Students will also demonstrate knowledge of the strategic uses of data. |
| Foundational Statistical/Quantitative Skills | Students will be able to prepare data for statistical analysis, perform basic exploratory and descriptive analysis as well as employ foundational statistical techniques needed to analyze data. |
| Advanced Statistical/Quantitative Skills | Students will be able to build and interpret advanced predictive models. Students will be able to combine business rules and mathematical models to optimize business decisions from data. |
| Ethical Awareness | Students will be able to articulate an understanding of ethical issues in all phases of business analytics with particular emphasis on the new possibilities afforded by the emergence of big data. |
| Professional Communication | Students will be able to explain complex analytical models and their results orally and in writing to technical and non-technical/lay audiences. |
| Knowledge Integration | Students will be able to apply the three key types of analytics (descriptive, predictive, and prescriptive) in a business domain to add value to business decision-making. |
MS in Business Analytics Curriculum
Courses in Specialization (33 - 34 credits) Required (21 credits) | ||
| BUS 9420* | Communications and Ethics for Business Analytics | 3 credits |
| STA 9661 | Applied Statistics for Business Analytics | 3 credits |
| CIS 9340 | Principles of Database Management Systems | 3 credits |
| CIS 9650 | Programming for Business Analytics | 3 credits |
| CIS 9660 | Data Mining for Business Analytics | 3 credits |
(OR) | Management Science (OR) Intro to Quantitative Modeling | 3 credits |
| BUS 9430** | Business Analytics Project Lifecycle Management | 3 credits |
*Students who intend to pursue a career in accounting can substitute BUS 9420 with BUS 9557 Managerial Skills for Accountancy Professionals with the permission of an academic advisor (ZicklinMSPrograms@baruch.cuny.edu). ** Required Capstone course | ||
Concentration in Data Analytics Take the two required courses (6 credits) below and 6 credits from the list of electives to complete the Data Analytics concentration | ||
| CIS/STA 9760 | Big Data Technologies | |
| CIS 9655 | Data Visualization | 3 credits |
| 3 credits | ||
Concentration in Marketing Analytics Take the two required courses (6 credits) below and 6 credits from the list of electives to complete the Marketing Analytics concentration | ||
| MKT 9737 | Marketing Analytics | 3 credits |
| MKT 9738 | Web Analytics and Intelligence | 3 credits |
| Free Electives (6 credits) | ||
| CIS 9440 | Data Warehousing and Analytics | 3 credits |
| CIS 9655 | Data Visualization | 3 credits |
| CIS 9310 | Object-Oriented Programming I | 3 credits |
| CIS/STA 9760 | Big Data Technologies | 3 credits |
| CIS/STA 9665 | Applied Natural Language Processing | 3 credits |
| STA 9797*** | Advanced Data Analysis | 3 credits |
| STA 9890*** | Statistical Learning for Data Mining | 3 credits |
| STA 9891*** | Machine Learning for Data Mining | 3 credits |
| STA 9701*** | Times Series: Forecasting and Statistical Modeling | 3 credits |
| OPR 9730*** | Simulation Modeling and Analysis | 3 credits |
| MKT 9780 | Digital Marketing | 3 credits |
| MKT 9782 | Search Engine Marketing | 1.5 credits |
| MKT 9783 | Social Media Marketing | 1.5 credits |
| MKT 9785 | Digital Marketing Strategy | 3 credits |
| MKT 9737 | Marketing Analytics | 3 credits |
| MKT 9738 | Web Analytics and Intelligence | 3 credits |
| MKT 9740 | Data-driven Marketing Strategy | 3 credits |
| MKT 9741 | Marketing Analytics with Big Data | 3 credits |
| STA 9713*** | Financial Statistics | 3 credits |
| ECO 9723*** | Econometrics - Theory and Applications I | 3 credits |
| FIN 9770*** | Corporate Finance | 3 credits |
| ACC 9806*** | Financial Statement Analysis and Reporting | 3 credits |
| ACC 9886*** | Data Analytics in Accounting | 3 credits |
| TAX 9861*** | Federal Income Taxation: Theory and Practice | 3 credits |
| ***Electives have additional prerequisites but may be of interest to students who have the necessary background. Students may substitute elective courses with ACC/TAX designation with other advanced accounting or tax courses based on their background. | ||