10 Best Master’s in Data Analytics

Appalachian State University offers a Master of Science in Applied Data Analytics designed to prepare students for high-demand careers in data science. The program emphasizes individualized attention, providing resources like career services, academic advising, and professional development opportunities. The program is ranked 11th in the nation by Fortune Education and is housed in the Walker College of Business, which is consistently recognized by sources like U.S. News & World Report and The Princeton Review.

Students can choose from several concentrations:

• Interdisciplinary Analytics: Focuses on data management, visualization, and strategic decision-making.
• Supply Chain Analytics: Enhances operational efficiency through data-driven decisions.
• Sustainability Analytics: Trains students to analyze sustainability indicators and report findings.

Key Features:

• Completion Time: 1 year (full-time) or 2 years (part-time).
• Dual degree options combining data analytics with fields like business administration or public administration.
• Graduate assistantships and professional development resources available.

Career paths include:

• Data Scientist
• Marketing Analyst
• Supply Chain Manager

With an average data analyst salary of $103,500, this program offers strong career prospects. Interested students can apply for admission by key deadlines, with options for GRE/GMAT waivers available.

Oklahoma State University’s Master’s in Business Analytics and Data Science (MS BAnDS) program is a STEM-designated degree that trains students to address real-world problems using data science and analytics. The program is ranked among the top in the nation, including 9th by Fortune for best master’s programs in data science.

Students gain hands-on experience with industry-leading software like Python, R, SQL, and Tableau, which helps them stand out in the job market. The program also offers opportunities to specialize in various fields or tailor a unique set of electives based on career goals.

Key Features:

• Duration: 21 months
• Tools and Software: Includes Alteryx, Azure, Snowflake, TensorFlow, and more.
• Rankings: 9th by Fortune, 19th by TFE Times
• Admission Requirements:
  • GMAT/GRE scores (waivers available for eligible applicants)
  • Personal statement
  • 3 letters of recommendation
  • TOEFL/IELTS (for international students)

The program is designed to accommodate internships and research opportunities that enhance students’ learning and employability. Graduates typically pursue careers as data scientists, business analysts, or consultants in diverse industries.

The University of North Texas offers a Master of Science in Advanced Data Analytics designed to give students the essential skills they need to succeed in data science. This 30-hour program combines coursework in big data, machine learning, cloud computing, and data visualization with practical business case studies. Students can specialize in areas like:

• Digital Retailing
• Health Data Analytics
• Management and Statistics

They can also create a personalized focus with the help of an advisor.

Key Highlights:

• Flexible Formats: Available online or in-person with accelerated 8-week sessions and five start times per year.
• Completion Time: As little as 12 months with the accelerated online format.
• Core Skills Developed:
  • Extracting actionable insights from data.
  • Building predictive models using machine learning.
  • Creating effective visualizations for business communication.
  • Utilizing cloud-based tools for data storage and processing.

Students engage in hands-on projects, culminating in an analytics capstone course instead of a traditional thesis. This program is ideal for those looking to advance in their current careers or transition into new roles in industries that require data expertise.

Indiana University’s residential Master of Science in Data Science program offers an immersive experience on the Bloomington campus, attracting students from around the world. The program provides access to renowned faculty and state-of-the-art research facilities, fostering interdisciplinary collaboration. Students gain foundational knowledge and practical skills through hands-on projects, internships, and partnerships, preparing them for real-world challenges.

Key highlights of the program include:

• Core Competencies: Programming, statistics, data analytics, machine learning, data wrangling, data visualization, communication, business foundations, and ethics.
• Flexible Learning Tracks: Choose from Applied Data Science, Big Data Systems, Computational and Analytical, or Managerial Data Science.
• Career Preparation: Emphasis on building marketable skills through collaborative research and interdisciplinary coursework.
• Special Opportunities: Participation in the South Korea/U.S. Global Lab program and the Indiana Genomics Research Training Program.

To graduate, students must complete 30 credit hours and select coursework aligned with their career goals. The program is STEM-eligible, making it an attractive option for international students. Indiana University’s data science program is ranked among the top in the nation, providing a solid foundation for a successful career in the field.

The Master of Science in Data Science and Analytics at the University of Missouri (MU) focuses on providing students with both technical skills and real-world experience. The program is flexible, offering online and on-campus options. Students are required to complete 30 credit hours, including a core curriculum and specialized courses in one of several emphasis areas.

Program Details:

• Credits Required: 30 hours
• Core Curriculum: 16 credit hours
• Emphasis Areas: BioHealth Analytics, Geospatial Analytics, High-Performance Computing, Strategic Communication & Data Journalism, Human-Centered Science Design
• Capstone Project: 3 credit hours (or 6 credits for thesis research, if on-campus)

The program emphasizes a collaborative approach to data science, encouraging teamwork and communication. Students gain hands-on experience with large datasets and cutting-edge tools. Additionally, the curriculum includes training in data storytelling, version control (using Git), and soft skills.

Key Features:

• Flexible online and on-campus formats
• Industry engagement through spring executive sessions
• STEM-OPT eligible for international students

MU’s data science program is designed for students from diverse backgrounds, fostering a strong learning community where collaboration and practical applications are central to the experience.

The University of California, Irvine (UCI) offers a Master of Data Science (MDS) program. This program is designed to integrate key concepts from statistics and computer science, providing students with the skills necessary to thrive in a world increasingly driven by artificial intelligence (AI) and data analysis.

Program Highlights:

• Flexible Learning Paths: Students can choose between a 15-month full-time or a 24-month part-time schedule.
• Comprehensive Curriculum: The program consists of 52 units, including ten core courses, three electives, and a capstone project.
• STEM Designation: Graduates are eligible for up to 36 months of Optional Practical Training (OPT).

The UCI MDS program is particularly notable for its strong emphasis on hands-on training in areas such as statistical modeling, machine learning, data management, and AI. Students work on real-world problems through two capstone projects, gaining practical experience that enhances their employability.

Advantages of the Program:

• High Placement Rate: 85% of graduates find employment within three months of graduation.
• Industry Connections: The program benefits from UCI’s location in Southern California’s TechCoast, which is home to numerous high-tech and biomedical companies.
• Access to Resources: Students have opportunities to engage with local businesses and industries, access valuable resources, and foster innovation.

Graduates of the MDS program will be well-equipped to contribute to the development of intelligent systems and pursue successful careers in data science.

The University of Arizona offers a Master of Science in Data Science (MSDS) program, designed to equip students with the skills needed for careers in one of the fastest-growing fields. The program is available both on-campus in Tucson and online, and it can be completed in 18 months by full-time students. The curriculum includes core courses in data mining, data analysis, visualization, and data ethics. Students can also choose from a range of electives like machine learning, artificial intelligence, and natural language processing.

Key Points:

• Program Structure: 30 units required, including an internship or capstone project.
• Delivery: Available on-campus and online.
• Core Courses: Data mining, analysis, visualization, and ethics.
• Electives: Neural networks, AI, machine learning, and more.
• Career Outcomes: Roles include data scientist, AI engineer, machine learning engineer, and statistician.

Tuition varies depending on residency and the mode of study, with in-state on-campus tuition at $7,544.48 per semester and online tuition at $6,708 for 9 units. The program prepares graduates for diverse and in-demand roles across various industries.

The University of Delaware offers a Master of Science (M.S.) in Data Science, designed to provide students with a deep understanding of the methods behind data analysis and software. The program offers flexibility in both coursework and delivery, allowing students to study full-time or part-time with some online classes available. The curriculum covers key areas such as probability, statistics, machine learning, databases, and ethics. This comprehensive training prepares students for various roles in the growing field of data science.

Key Features:

• Program Length: Complete in 3-4 semesters.
• Flexible Study Options: Full-time, part-time, and some online classes.
• Customizable Degree: Tailor your coursework to match your career goals.
• Faculty Support: Benefit from mentorship by over 60 affiliated faculty from 20+ departments.

Graduates of this program are well-prepared for careers as data analysts, data engineers, or data scientists. They find employment in top organizations such as JPMorgan Chase, Wells Fargo, and Bank of America. The job outlook for data scientists is strong, with a projected 36% growth in employment from 2021 to 2031, and a median salary of $120,000.

The Master of Science (MS) in Data Science at the University of Minnesota offers students a comprehensive education in big data and its analysis. This program involves collaboration with experts from various fields, including the College of Science and Engineering, the Institute of Health Informatics, and the School of Public Health’s Division of Biostatistics. Students are trained in advanced techniques for handling large datasets and exposed to the latest methods and theories, preparing them for future technologies in data science.

Key components of the program include:

• Courses in three main focus areas: statistics, algorithmics, and infrastructure/large-scale computing.
• Elective courses that allow students to tailor their education to their interests.
• Opportunities for research under faculty guidance.
• A capstone project, which is showcased at the annual Data Science Poster Fair.

The program is designed to provide a solid foundation for careers in data science, emphasizing practical experience through research and project work.

Penn State offers two graduate programs in Data Analytics: the Master of Science (MS) and the Master of Data Analytics (MDA). Both programs focus on equipping students with skills to analyze and interpret large datasets across different domains.

Key Points:

• Master of Science (MS): A research-focused program that includes core courses, electives, and a thesis project.
• Master of Data Analytics (MDA): An interdisciplinary program that covers data collection, classification, analysis, and modeling.
• Specializations: The MDA offers specializations in Business Analytics, Marketing Analytics, and Big Data Systems.
• Admission Requirements: Applicants need a relevant undergraduate degree, work experience, a statement of goals, and letters of recommendation. GRE/GMAT scores are required for the MS but not for the MDA.
• Curriculum: Both programs require at least 30 credits, including core courses and a capstone or thesis project.

These programs prepare graduates for roles like Data Analyst, Data Scientist, or Business Intelligence Developer by providing a strong foundation in data analytics and practical experience through projects.