Concentrations are available in:
The Master of Science in Data Analytics program provides students with the critical skills necessary to become a
Data Analyst or Data Scientist working in a variety of fields across all industries. The integration of Data Analytics
and Informatics has created a demand for professionals who can make data-driven decisions that propel their organizations forward.
This online/real-time and/or in-class M.S. in Data Analytics program prepares graduate students to make sense of real-world situations, conditions, and frequent everyday activities by synthesizing and mining big data with the intention of uncovering patterns, relationships, and trends. Big data has emerged as the driving force behind critical business decisions. Advances in our ability to collect, store, and process different kinds of data from traditionally unconnected sources enables us to answer complex, data-driven questions in ways that have never been possible before.
Data analytics combines information management, statistics, analytical thinking, quantitative methods, data modeling, data warehousing, and data mining to produce visualizations and other business intelligence models that help organizational leaders predict and evaluate best practices.
Data Analytics Program Requirements
Required courses for both concentrations.
Database Concepts & Design
- This course covers the database concepts that are the foundation and building blocks of sound database design and management. It explains why good database design is critical to the accurate and efficient storage and retrieval of data. The course will explore database design techniques such as database models, database modeling/design tools. The course identifies the functions provided by a database management system to help ensure the integrity of data. It teaches students how to design a database that maximizes data integrity using normalization techniques. It also covers the use of SQL to create and populate tables and retrieve and update data.
Statistics for Data Analytics
- This course introduces univariate data analysis methods using statistics. Data visualization methods and practices, and an overview of sampling techniques for data collection. Specifically, this course teaches introductory statistical methods for the analysis and visualization of data and basic concepts of probability theory. Course topics include descriptive statistics, data visualization techniques, an introduction to statistical inference (confidence intervals and hypothesis testing) for decision making, linear regression models, data sampling techniques. The students will learn the statistical package SPSS to analyze data sets from real-world applications which will be discussed in class.
Multi-Dimensional Analytics and Visualization
- The course introduces the practice of managing data as corporate assets by organizations to gain competitive advantage and meet regulatory demand. The course will also describe the data management emerging profession, and skills required to perform the various data management functions for each role.
Prerequisite: MSIN 615
Principles of Data Analytics
- This course is a hands-on introduction to the field of Data Analytics where students will learn the concepts and tools needed throughout the analysis process from formulating the research question to obtaining, cleaning, and collating data to making inferences and publishing results. Students will also learn how to formulate research questions in “data terms” so that it can be analyzed and identify the limitations imposed by the available data. Students will become versed in sorting data, filtering data and creating data totals. They will learn how to use Pivot Tables. They will also master Statistical Functions, Text Functions, Database Functions, Lookup Functions, and Date and Time Functions among others. Students will be introduced to data types, control structures, functions, and debugging tools. They will learn how to acquire data, what it means to clean data by removing inconsistencies and reformat data so that it can be analyzed by statistical tools.
Corequisite: MSIN 616
Thesis course required for both concentrations
Data Analytics Internship
- This course provides students with the opportunity to work as an intern in the Data Analytics area, and then to formulate a paper or project based on the approved internship. The internship must be pre-approved and should provide the student with the ability to combine his/her conceptual, technical, and applied knowledge in a business environment. This internship should draw on the skills and knowledge gained throughout the program. Regular progress reporting is expected throughout the internship.
Pre- or Corequisite: Permission of the Program Chair
Advanced Research in Data Analytics
- The Advanced Research course is designed to give students an individualized research, project including reading and reporting on a specific topic approved by an instructor. The subject, topics and related material must be relevant and advanced regarding data analytics either from a technology perspective or from a business perspective depending on the student's area of concentration.
Select One Concentration in M.S. in Data Analytics
See your selected concentration section to determine which required and elective courses you will need to take in your chosen area of study.