I knew Tiffin University was the place for me the second I stepped foot on campus. I toured a handful of other universities offering similar programs, but TU was the only school that truly made me feel at home.
-Caleb Reynolds '15
More than ever, today’s global economy requires a deeper understanding of products, customers, competitors and strategies. The world of business is quickly converging to a personalized market for goods and services that requires a thorough understanding of what customers want, when they want it and where they want it.
The goal of the TU MBA Data Analytics concentration is to introduce students to the tools and techniques that Data Analysts use to examine data in order to draw meaningful and actionable conclusions. Students will learn how to gather data, examine the suitability of the data, determine relevant models, calculate parameters of the models using software, interpret and communicate the results and suggest strategies to improve business performance.
Tiffin University’s School of Business is accredited by the Accreditation Council for Business Schools and Programs (ACBSP). The ACBSP is a leading specialized accreditation body for business education supporting, celebrating and rewarding teaching excellence. They accredit business education programs at the associate, baccalaureate, masters and doctorate degree levels worldwide. Institutions with this accreditation are committed to continuous improvement that ensures their business program will give students the skills employers want. Every quality business program worldwide is accredited.
Data Analytics Concentration 12 hours
MBA Core Curriculum 24 hours
**MBA core courses required of non-business undergraduate majors, international students and special admit applications.
Total MBA 36 hours
This is a sample course sequence to illustrate course offerings for this major. Consult the official Academic Bulletin for detailed registration and advising information.
On Campus - Offered in two terms per semester starting in January, May, August and October
Online - Offered in two terms per semester starting in January, March, May, July, August and October
- Core MBA, Leadership & Change and Data Analytics courses are offered online or on campus; remaining concentration courses are offered exclusively online.
Database Design and Data Modeling (DAX511) - This course will investigate principles and practices of database management and design. Student will compare and contrast relational database design, normalization, SQL queries, reports and other interfaces to database data, and documentation. Examination of public sources of data will lead to the practice of applying data sources in real-world examples. This course will utilize spreadsheet (i.e. Microsoft Excel) and database (i.e. Microsoft Access) technology currently used in organizations by applying functions in key field areas such as pivot tables, charts, queries, reports, macros, data load utilities, records and modules.
Applied Statistics for Data Analytics (DAX521) - This course will explore techniques to analyze data, produce graphical illustrations and draw conclusions using statistical, data analysis and visualization software packages. Focusing on the central tendency, data exploration and analytics, probability distributions and random variables, students will compare and contrast the basics of statistical inference, testing hypothesis and building confidence intervals, correlation and causation, and simple and multiple regression analysis.
Advanced Data Analysis Techniques (DAX631) - This course prepares students for analyzing data using advanced data analysis software and techniques to make decisions on data. Topics include Multivariable Regression, Non-Linear Regression, ANOVA, Cluster and Factor Analysis and Logistics Regression.
Data Visualization, Design and Presentation (DAX641) - This concentration capstone course will synthesize the previous learning outcomes in the Data Analytics Concentration to compose and construct a final project demonstrating application of data presentation and design. The design of the final project will focus on visualizing data analysis in real-world application by combining techniques of data modeling and data analytics; data processing; mapping data attributes to graphical attributes; and, constructing strategic visual encoding based on known properties of visual perception. Additionally, students will justify the effectiveness of visualization designs and critical thinking necessary in design decisions. Students will create their own data visualizations, and learn to use visualization tools and software.