Master of Science in Data Analytics Online

Feed your passion for data science and applied technology by learning industry-leading methods to identify, collect, analyze and transform data that create insights to help businesses and other organizations make informed decisions.

Apply by: 1/3/25
Start class: 1/13/25 Apply Now Apply Now

Program Overview

Discover our online M.S. in Data Analytics

The Master of Science in Data Analytics online program from Northwest Missouri State University readies you for a rewarding career using technology techniques to identify, collect, analyze and transform data. Besides acquiring experience in top programming languages, you will also gain hands-on practice with leading data analysis software and platforms. This online program is taught by experienced and dedicated faculty who will support your master's degree studies from start to finish. You can complete this online program in as few as 12 months.

The comprehensive curriculum in this master's in data analytics online program prepares you to contribute your expertise by learning how data affects decision-making through real-life project experiences.

Wondering how our M.S. in Data Analytics is different from our MBA in Business Analytics? As a graduate of the M.S. in Data Analytics, you will be prepared to work with large data sets, typically in a technical role, using data science to discover data-driven solutions. As a data analyst, you would present the information needed for organizations to make informed decisions. Comparatively, our MBA in Business Analytics would develop your understanding of how data impacts decisions and strengthen your ability to communicate effectively across all levels of business.

Graduates of this master's in data analytics online program will be able to:

  • Identify and evaluate moral and ethical issues in data analysis
  • Gain experience in top programming languages such as Python™ and SQL
  • Select the appropriate tools for analyzing data that helps businesses and organizations make informed decisions
  • Locate, extract and transform raw data into useful information
  • Apply descriptive and prescriptive analytic techniques to offer possible solutions to business problems
  • Construct and present compelling visuals to communicate a data-driven story
  • Gain familiarity in using data analysis software and platforms to**:
    • Process static data and streaming data to gain useful, actionable insights
    • Process data locally and on major cloud platforms (e.g., Amazon, Google Cloud Platform, Microsoft Azure)
    • Process data using popular analytics services, platforms, and APIs (e.g., Apache Kafka, Apache Spark, Apache Beam, Splunk, Tableau)
    • Process data using popular relational and NoSQL datastores (e.g., PostgreSQL, mySQL, MongoDB)
    • Collaborate professionally using modern version control systems and code hosting platforms (e.g. Git, GitHub, BitBucket)
  • Plan and execute an independent, real-world project using what you've learned about data analytics throughout the online program
Graduates of this master's in data analytics online program will be able to:
  • Identify and evaluate moral and ethical issues in data analysis
  • Gain experience in top programming languages such as Python™ and SQL
  • Select the appropriate tools for analyzing data that helps businesses and organizations make informed decisions
  • Locate, extract and transform raw data into useful information
  • Apply descriptive and prescriptive analytic techniques to offer possible solutions to business problems
  • Construct and present compelling visuals to communicate a data-driven story
  • Gain familiarity in using data analysis software and platforms to**:
    • Process static data and streaming data to gain useful, actionable insights
    • Process data locally and on major cloud platforms (e.g., Amazon, Google Cloud Platform, Microsoft Azure)
    • Process data using popular analytics services, platforms, and APIs (e.g., Apache Kafka, Apache Spark, Apache Beam, Splunk, Tableau)
    • Process data using popular relational and NoSQL datastores (e.g., PostgreSQL, mySQL, MongoDB)
    • Collaborate professionally using modern version control systems and code hosting platforms (e.g. Git, GitHub, BitBucket)
  • Plan and execute an independent, real-world project using what you've learned about data analytics throughout the online program

Data analytics career opportunities include:

  • Computer and Information Systems Manager
  • General and Operations Manager
  • Management Analyst
  • Information Scientist
  • Actuarial Analyst
  • Business Analyst
  • Business Intelligence Analyst
  • Crime Data Analyst
  • Data Analyst
  • Financial Analyst
  • Reporting Analyst
  • Information Technology Project Manager
Graduates of this master's in data analytics online program will be able to:
  • Computer and Information Systems Manager
  • General and Operations Manager
  • Management Analyst
  • Information Scientist
  • Actuarial Analyst
  • Business Analyst
  • Business Intelligence Analyst
  • Crime Data Analyst
  • Data Analyst
  • Financial Analyst
  • Reporting Analyst
  • Information Technology Project Manager
Graduates of this master's in data analytics online program will be able to:

Accreditation:

AAQEP logo

Northwest Missouri State University is accredited by the Association for Advancing Quality in Educator Preparation (AAQEP) and is recognized by the Missouri Department of Elementary & Secondary Education™ (DESE) and the Higher Learning Commission.

Also available

Northwest offers a variety of specialized online graduate studies program options. Check out our other online graduate studies programs.

Total Tuition $11,730*
Program Duration As few as 12 months
Credit Hours 30
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Need More Information?

Call 844-890-9304

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Tuition

Pay for your online program by the course

Our M.S. in Data Analytics online program offers affordable, pay-by-the-course tuition, which is the same for in-state and out-of-state students. All fees are included.

View additional tuition information+

Program Per Credit Hour Per Course Per Program*
M.S. in Data Analytics $391 $1,173 $11,730

Important Refund Information

2nd day of class Last date for 100% refund for dropped course
4th day of class Last date for 75% refund for dropped course
6th day of class Last date for 50% refund for dropped course
8th day of class Last date for 25% refund for dropped course


Tuition breakdown:

Total Tuition $11,730*
Per Credit Hour $391

Transfer your credits for lower tuition

Use our Tuition Estimator to see how affordable your degree could be. Slide the notch to the number of credits you've already earned—which may qualify for transfer credit—to get an estimate of what your degree might cost.

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Your Estimated Tuition: $16,140
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Transcripts sent from other colleges and universities will be evaluated, and accepted credits will be added to the student's A-State record. The Tuition Estimator is not a guarantee or predictor of the number of credit hours that will be accepted.

Calendar

Dates you need to know

Northwest online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.

View full calendar  + 

TermProgram Start DateApplication DeadlineDocument DeadlineRegistration DeadlinePayment DueLast Class Day
Spring 11/13/251/3/251/6/251/7/251/8/252/28/25
Spring 23/10/252/24/252/27/253/3/253/5/254/25/25
Summer 15/5/254/21/254/24/254/28/254/30/256/20/25
Summer 26/23/256/6/256/11/256/13/256/17/258/8/25
Fall 18/25/258/11/258/14/258/18/258/20/2510/10/25
Fall 210/20/2510/6/2510/9/2510/13/2510/15/2512/5/25

Now enrolling:

Next Apply Date: 1/3/25
Next Class Start Date: 1/13/25
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earning your degree?

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Admissions

Requirements for the M.S. in Data Analytics online program

At Northwest, we've streamlined the admission process to help you get started quickly and easily. Please read the requirements for the M.S. in Data Analytics online, including what additional materials you need and where you should send them.

Admission Requirements:

  • Bachelor’s degree from a regionally accredited institution
  • GPA of at least 2.75 on a 4.0 scale
  • Official transcripts from all institutions attended
  • GRE/GMAT waivers available
View all admission requirements +

To apply for this program, you must meet these requirements:

  • Bachelor's degree from a regionally accredited higher education institution
  • Cumulative GPA of 2.75 or higher on the undergraduate transcript
  • Documentation of one of the following:
    • GRE combined score of 285 or higher
    • GMAT total score of 440 or higher

GMAT Waiver Information

To apply to the M.S. in Data Analytics online degree program without submission of a GMAT or GRE score, you must have a bachelor's degree with a cumulative GPA of 2.75 on a 4.0 scale from a regionally accredited university plus one of the following:

  • Cumulative GPA of 3.25 or higher on the undergraduate transcript
  • Master's degree from a regionally accredited institution with a cumulative GPA of 3.0 or higher
  • Three years of full-time work experience

If you are a non-Missouri student, you should determine whether this program fits the certification requirements for your state.

Official transcripts can be emailed to [email protected]. To submit official documents by mail, send them to:

Graduate Records Specialist
Northwest Missouri State University
800 University Drive
Maryville, MO 64468-6001

Have a question? Call us at 844-890-9304.

Click here for State Authorization information.


Admission Requirements:

  • Bachelor’s degree from a regionally accredited institution
  • GPA of at least 2.75 on a 4.0 scale
  • Official transcripts from all institutions attended
  • GRE/GMAT waivers available

Courses

Read about our data analytics online classes

For the M.S. in Data Analytics online, the curriculum is comprised of 10 courses (30 credit hours).

Expand All
Duration: 7 Weeks weeks
Credit Hours: 3
This course will introduce students to basic statistics from a data science perspective. Statistical methods are a key part of data science. The primary objective of this course is to explain how to apply various statistical methods to data science, how to avoid their misuse and to give advice on what is important and what is not. Topics include exploratory data analysis, data and sampling distributions, statistical experiments and significance testing, regression and prediction, classification, statistical machine learning, and unsupervised learning. It starts with simple statistics and then move on to statistical methods used in data science algorithms. The concepts learned in this course should help students learn the statistical techniques required to implement data evaluation in data science tasks such as data cleaning, mining, and analysis.
Duration: 7 Weeks weeks
Credit Hours: 3
This course offers an introduction to the concepts and implementation of systems for continuous intelligence and interactive analytics. It includes ingesting and processing raw data and presenting evolving analytics in engaging, easy-to-understand, actionable formats.
Duration: 7 Weeks weeks
Credit Hours: 3
This course covers the design and development of exploratory diagrams and graphics for various data sets. The course may include concepts such as chart and graph design, networks, topological graphs, display of multi-dimensional data, effective use of space and color, animations, interactive visualizations, mapping, cartography, web data acquisition, and advanced visualization tools. Prerequisite: Coursework equivalent to general statistics and programming.
Duration: 7 Weeks weeks
Credit Hours: 3
This course provides an introduction to accessing, manipulating, and presenting data from a variety of web-based sources. APIs (social media) and web scraping will be used as a platform to practice the fundamentals of applied Natural Language Processing. Students will gain experience extracting and presenting information from semi-structured and unstructured data sources.
Duration: 7 Weeks weeks
Credit Hours: 3
This course provides foundational skills needed in subsequent courses and includes an introduction to descriptive and predictive analytics. It includes a review of basic statistics, and introduction to widely-used data analysis tools. The course focuses on key foundations of importing, querying, and processing data and characterizing and visualizing information.
Duration: 7 Weeks weeks
Credit Hours: 3
This course explores data from both a storage and analytical perspective. Topics such as relational and non-relational database functionality and constraints, local and cloud database considerations, relevant data types, and data manipulation are included. Students will receive hands-on experience working with relational, non-relational databases and data manipulation tools.
Duration: 7 Weeks weeks
Credit Hours: 3
Students will use machine learning models to build tools to perform novel analyses of data sets. Topics will include data acquisition and cleaning, selecting and evaluating predictive models, regression models, classification models, and deep learning with neural nets. Prerequisite: CSIS 44608 Data Analytics Fundamentals.
Duration: 7 Weeks weeks
Credit Hours: 3
This course provides an introduction to the principles, properties, and tools of streaming data in the context of analytics. Students will learn how to understand, process, extract insights, and respond to massive volume and high-rate data generated from a variety of sources such as real-time business transaction and social media networks using streaming data models, approaches, languages, and processing tools. Prerequisite: CSIS 44661 Databases for Analytics.
Duration: 7 Weeks weeks
Credit Hours: 3
This course will introduce students to various techniques available to extract suitable information (business intelligence, BI) from the large volume of data an organization can use to help managers make better business decisions.
Duration: 7 Weeks weeks
Credit Hours: 3
This course serves as the capstone experience for the M.S. in Data Analytics program. It is a project course that integrates the knowledge from the rest of the Data Analytics program and applies it to a real-world dataset. This course covers the full spectrum of applying analytics from identifying the business needs, acquiring data, storing/streaming data, analyzing data using various machine learning algorithms, and communicating results with appropriate charts to support better decision making. Prerequisites: Completion of at least 24 hours of graduate credit toward the graduate MS Analytics program and approval by the graduate advisor.

Ranked #1

Northwest Missouri State University is ranked #1 among the "Best Online Colleges in Missouri" by SR Education Group (2020)

Highly Qualified Faculty

100% of classes are taught by professionals, not graduate assistants

*Tuition and fees are based on current rates. Textbooks and laptops are not included with tuition.

**Most software will be free for student use, but there might be nominal fees associated with some of these.

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