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New football field named after DSU Coach George Blankley. The Trojans Unite campaign will focus on several areas, one of those key areas being athletic facilities.

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Home ― Master of Science in Analytics (MSA)

Master of Science in Analytics (MSA)

Transform the world with analytics

In the workforce, the progression of big data careers continues to grow. Professionals with advanced training are needed to solve crucial data-driven issues and assist with analytic-driven decisions. Join a multidisciplinary field and transform the world.

Elevate your knowledge with the newest technology, like SAS, Python, and R. Discover Big Data Analytics using Hadoop, Spark, and Kafka, business intelligence and visualization, deep learning, and more.

Apply appropriate techniques and tools to solve issues. Modify big data sets into actionable information. Obtain a good understanding of information technology and computer languages. Assess alternative approaches, manage projects, and interpret results of analysis.

Next Steps

College of Business and Information Systems

Specialize your degree

Focus your degree in one of our four-track options:

  • Business
  • General
  • Health care analytics
  • Information systems
An example of data visualization.

Understanding messy data

Large amounts of data – referred to as messy data – can be hard to understand, but they also present opportunities to learn and make decisions. Students in our Master of Science In Analytics program learn to present this information in helpful data visualizations.

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Learning outcomes

Upon completion of the MS degree in Analytics, students will:

  • Be able to prepare and transform big data sets into actionable information in an easy-to-understand format to support analytics through the use of advanced data processing tools
  • Be able to select the appropriate analytics techniques and apply advanced analytical tools to solve data analytics problems
  • Be able to demonstrate a good understanding of using information technology and computing languages to implement analytics solutions
  • Be able to assess alternative approaches and infrastructures for implementing big data analytics
  • Be able to manage data analytics projects to ensure delivery of a successful data analytics initiative throughout its life cycle
  • Be able to interpret the results of the analysis