Data Analytics M.S.

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Availability
Available - On Campus
Available - Online
Program Credits
30

Taught by experienced faculty, the M.S. in Data Analytics gives students actionable insight that provides a real competitive advantage in a data-driven world.

This program extends the concepts in systems analysis and information systems management to the tools, concepts, and processes used to collect, analyze, store, and support organizational decisions from external information sources.

Program Overview 

The MS in Data Analytics builds the knowledge of data analytics, data visualization and other tools used in all types of analytics. The program emphasizes applied skills: the students will learn to apply the appropriate platforms and models in analytics tasks.

  • Flexible Curriculum: This degree program includes seven required courses, leaving room for three additional courses that match your specific area of interest, such as Cybersecurity, Artificial Intelligence/Machine Learning or Cloud Computing.
  • Applied Knowledge and Skills: Gain applied data analytics and visualization knowledge and skills through learning multiple relevant applications such as MS Power BI, Tableau, Jupyter Notebook, cloud services and much more. 
  • Scholar-Practitioner Faculty: Study with professors who have strong theoretical and practical knowledge of data analytics.
  • Additional Credential:  Earn an additional credential to advance your career by adding a certificate to your graduate course planning. This program has enough elective courses to combine it with a certificate in Cybersecurity.
  • High Job Placement Rate: Data analysts are in great demand! Graduates of this program have assumed multiple data analytics positions.
  • On Campus and Fully Online: Complete your degree on campus, or fully online-anywhere/anytime.

$99,500* Average Salary

Possible career paths:

  • Data Analyst
  • Cloud Data Analyst
  • Healthcare Data Analyst
  • Data Analytics Engineer
  • Consumer Research Data Analyst
  • Business Intelligence Strategist
  • Data Quality Manager

* per the US Bureau of Labor for management and data analysts

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Admissions Requirements

  • A completed application. Apply at: rmu.edu/apply
  • Official undergraduate transcripts from all colleges and universities attended. Transcripts from schools outside the U.S. must have transcripts evaluated by World Education Services (WES) or other National Association of Credential Evaluation Services (NACES) member organizations.
  • GPA: 3.0 or above

Contact Us

Dr. Natalya Bromall
Director, CIS Graduate Programs
412-397-6435
bromall@rmu.edu 

Degree Requirements and Courses

View Guided Curriculum

  • INFS6010 Decision Support Systems
  • INFS6510 Introduction to Data Analytics
  • INFS6240 Database Management Systems
  • INFS6720 Data Mining
  • INFS6730 Data Integration for Analytics
  • INFS6241 Big Data Technologies
  • CYMS6210 Defending and Securing Networks
  •  INFS/CYMS6000-7000 Level Elective
  •  INFS/CYMS6000-7000 Level Elective
  •  INFS/CYMS6000-7000 Level Elective
  • INFS7000 Program Outcomes Assessment (0 credits)
Program Learning Outcomes

Through your course work, you will learn how to:

  • Understand and apply the process of decision-making and use decision support tools to
    facilitate decision-making in organizations.
  • Understand and apply database technologies, design, modeling, and SQL to the solution
    of business problems.
  • Apply network security defense tools to protect data at rest and data in transit by
    leveraging cybersecurity strategies.
  • Evaluate and apply various data analytics software tools and concepts to develop
    enterprise reporting, data visualizations, and executive dashboards for transforming and
    analyzing big data.
  • Evaluate and apply various data analytics software tools and concepts for model
    development and evaluation.
  • Compare and contrast the statistical techniques behind the wide variety of data mining
    algorithms and apply data mining tools and techniques to various business, scientific,
    and social problems.
Admissions, Tuition, and Scholarship Information
  • Prospective students should have an undergraduate GPA of 2.75 and above with a degree in computer science, information systems, mathematics, software engineering, or related fields.
  • Students from other fields are welcome to apply, but should note that some experience with introductory statistics is recommended.
Contact Us

Natalya G. Bromall, Ph.D.

Director, CIS Graduate Programs 
Professor of Computer and Information Systems

Email: bromall@rmu.edu 
Phone: 412-397-6435 
Office Wheatley Center 305

Jamie L. PinchotJamie L. Pinchot, D.Sc.

Department Head, Computer and Information Systems
Professor of Computer and Information Systems

Email: pinchot@rmu.edu
Phone: 412-397-6050 
Office: Wheatley Center 309

Sample Courses:

These are some of the classes for students in this academic program:

Data Mining
Data Warehousing
Geographic Information Systems

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School of Data Intelligence and Technology

School of Data Intelligence and Technology

In the School of Data Intelligence & Technology, students are immersed in cutting-edge programs that prepare them for careers in a variety of rapidly evolving fields. 

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