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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.

10/04/21 Next Application Due Date
10/18/21 Next Class Start Date

Overview

Discover Our Online M.S. in Data Analytics

The M.S. in Data Analytics online program 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.


$10,500 Total Tuition
As few as 12 months Program Duration
30 Credit Hours

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

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

Career opportunities include:

  • Computer and Information Systems Manager
  • General and Operations Manager
  • Management Analyst
  • Big-Data Architect
  • Logistician
  • Data Scientist
  • Information Scientist
  • Data Analyst
  • Financial Analyst
  • Chief Analytics Officer
  • IT Project Manager

Have questions or need more information about our online programs?

Also available

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

Tuition and Fees

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.

$350 Per Credit Hour
$10,500 Program Tuition*

View full tuition breakdown

Program Per Credit Hour Per Course Per Program
M.S. in Data Analytics $350 $1,050 $10,500

Important Refund Information

1st day of class Last date for 100% refund for dropped course
2nd day of class Last date for 75% refund for dropped course
3rd day of class Last date for 50% refund for dropped course
4th day of class Last date for 25% refund for dropped course

*Tuition and fees are subject to change. Current amounts are based on 2020-21 tuition rates. Textbooks and laptops are not included with tuition.

Northwest Missouri State University is ranked #1 among the "Best Online Colleges in Missouri" by SR Education Group (2019).

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.

10/04/21 Next Application Deadline
10/18/21 Start Classes

View full calendar

Term Program Start Date Application Deadline Document Deadline Registration Deadline Payment Due Last Class Day
Fall 1 08/18/21 08/04/21 08/10/21 08/11/21 08/13/21 10/08/21
Fall 2 10/18/21 10/04/21 10/08/21 10/11/21 10/13/21 12/10/21
Spring 1 01/12/22 01/04/22 01/04/22 01/05/22 01/07/22 03/04/22
Spring 2 03/14/22 02/28/22 03/03/22 03/08/22 03/09/22 04/29/22
Summer 1 05/10/22 04/26/22 04/29/22 05/03/22 05/05/22 06/24/22
Summer 2 06/27/22 06/13/22 06/16/22 06/20/22 06/22/22 08/12/22

Ready to take the next step toward earning your degree online from Northwest?

Admissions

Requirements for the Master’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. The requirements include:

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 844-890-9304.

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   |   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, then moves 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   |   Credit Hours: 3

This course focuses on IT product and service selection and evaluation based on financial considerations including return on investment, time cost of money, depreciation and system life. It includes key measurements for software development and project management as well as a methodology for selecting the best measurements. In addition, students will use Microsoft® Excel® extensively to build financial analysis models.

Duration: 7 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   |   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   |   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   |   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 and non-relational databases and data manipulation tools.

Duration: 7 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 44-608 Data Analytics Fundamentals.

Duration: 7 weeks   |   Credit Hours: 3

This course introduces 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 44-661 Databases for Analytics.

Duration: 7 weeks   |   Credit Hours: 3

This course will introduce students to various techniques available to extract suitable information (business intelligence) from the large volume of data an organization can use to help managers make better business decisions.

Duration: 7 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 M.S. in Data Analytics program and approval by the graduate advisor.

Still undecided?

Northwest offers a variety of specialized MBA options. Check out our other Graduate Studies online programs.

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