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Data Analytics


Program Title

Data Analytics

Degree Designation


Award Type

Post-Baccalaureate Certificate

Program Level


Instruction Mode

On Campus

Program Description

Designed for working professionals, the Data Analytics Certificate will allow graduates to use existing company data to summarize and make sense of the data, answer questions on company performance, solve problems, and predict growth. Students will recognize the types of problems data analytics can and cannot solve, discern how to securely use data, discover how to find and clean data, identify alternative data analytic techniques designed to make accurate predictions, and learn how to communicate the results of data analytics to others.



Herberger Business School




Free Form Requisites

Admissions Requirements

  • Undergraduate degree

  • Statistical experience equivalent to course/STAT 242 or equivalent course

  • Computer experience including familiarity with spreadsheet software such as Excel

  • Programming familiarity in SAS or other language equivalent to course or course

Program Requirements

IS 534, IA 658, STAT 615, ECON 670, STAT 660


Preferable to take course - Introduction to Data Analytics first and course - Data Visualization for Analytics last, with other courses in between. Preferable to have access to company data so a project using that data can be completed by the end of the certificate. Ideally sequencing is a 2-2-1 with course - Foundations and course - Best Practices in Data Management in the fall, course Advanced Economic and Business Forecasting and course Data Mining in the spring, and then course Data Visualization as the final course in summer.

See program website for additional information.

Program Learning Outcomes


Apply statistical or logical techniques to describe, evaluate, and analyze business data.


Use business analytics to formulate and solve business problems and make managerial decisions.


Evaluate data structures, data problems, storage and retrieval options, and data communication options.


Apply regression analysis, time series analysis and forecasting techniques to business data.


Organize and communicate complex information concisely.

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