Register By: August 10
Classes Start: August 12
Analyze Data for Businesses Big and Small with a Master’s in Data Analytics Online
The most successful businesses employ professionals to analyze data and find more efficient ways to operate. From global corporations and government agencies to small businesses, retail stores and nonprofit organizations, data analysis is core to daily function. The Master of Science in Data Analytics online program at SNHU can help you gain specialized skills in data analytics to fill these crucial roles.
Thanks to the explosion in the amount of data businesses use, the field of data analysis is among the fastest growing, with a large number of exciting, high earning job openings such as:
- Data Scientist
- Named "Sexiest Job of the 21st Century" by the Harvard Business Review*
- #5 on CareerCast's list of "The Best Jobs of 2017"*
- Analytics Manager
- #2 on CNN Money's list of "Fastest-Growing Jobs"*
- #5 on Glassdoor's "50 Best Jobs in America for 2017"*
SNHU's MS analytics degree is recognized by the Professional Science Master's (PSM) national office as a Professional Science Master's program. The PSM is an innovative degree designed to allow students to pursue advanced training in science or mathematics while developing workplace skills valued by employers.
See Yourself Succeed in Analytics
In as fast as 15 months, the 12-course master's in analytics core covers everything from Foundations of Data and Decision Methods and Modeling, to Presentation and Visualization of Data, Optimization and Risk Assessment, and Predictive Analytics.
SNHU’s master’s in analytics program goes beyond the traditional view of data collection and interpretation. You’ll develop concrete skills to apply to any work setting. Upon completion of the capstone in data analytics, you’ll come away knowing how to leverage data quickly and effectively, plus something even more valuable: how to help a wide variety of industries make mission-critical decisions, assess risk, operate more efficiently and compete more successfully.
As a private, nonprofit university, SNHU has one mission – to help you see yourself succeed. The benefits of earning your master’s in data analytics at SNHU include:
- Affordability. Take advantage of some of the most affordable tuition rates in the nation
- Convenience. Attend class when it’s convenient for you – online education means 24/7 access
- Efficiency and flexibility. Complete your graduate degree in as few as 15 months, with two courses per 10-week term
- Expert instruction. Learn from instructors with relevant, real-world experience
- Minimal requirements. No GMAT or GRE required for admission
- Networking. Tap into our nationwide network of alumni for internship and career opportunities
- Student support. Count on the ongoing support of dedicated academic and career advisors specialized in your area of study
Admission Requirements
Acceptance decisions are made on a rolling basis throughout the year for our 5 graduate terms. You can apply at any time and get a decision within days of submitting all required materials. To apply, simply contact an admission counselor, who can help you explore financial options. Your counselor can also walk you through the application process, which involves completing a graduate application ($40 fee) and providing undergraduate transcripts.
Candidates must also submit a professional resume.
Career Outlook
The demand for professionals with degrees in data analytics is growing every day. A study by IBM and Business-Higher Education Forum (BHEF) projects that the number of U.S. positions for data and analytics talent will increase 15% by 2020, with average salaries of just over $80,000.* Demand for operations research analysts, to cite just one example, is expected to grow 27% through 2026, according to the U.S. Bureau of Labor Statistics.*
Opportunities span a wide range of industries from finance to manufacturing, healthcare to government. In addition to becoming a research analyst or data scientist, graduates can look forward to a potential career as a:
- Data analyst
- Data engineer
- Statistician
- Data mining specialist
- Analytics manager
Curriculum
Our master’s in data analytics online program focuses on the strategic and advanced uses of data analytics across a broad range of industries. Courses cover data mining, visualization, modeling, optimization and the ethical uses of data.
View Full Curriculum in the Catalog
Courses May Include
DAT
510
Foundations of Data
We live in a world where substantial amounts of data are available at the touch of a button. While this may be a very empowering prospect, it can also be overwhelming. In this course, students will examine the status of Big Data and its impact on the business world, framing analytics challenges using a structured life cycle approach to data analytics problems. Emphasis will be placed upon the verification of data, analytic techniques and open source tools for analyzing data, the role of regulatory organizations, and the privacy and ethics issues that surround its use.
DAT
515
Enterprise Data Management
Understanding the complexity of current data management systems and the ever evolving technology necessary to leverage such data is essential in making sound data-driven decisions. In this course, students will examine the issues in managing data and information from an enterprise perspective, and explore data management as an essential resource to organizational success through a deeper understanding of the concepts and techniques for managing the design, development, and maintenance of all the components of enterprise information management. The course will examine the roles and responsibilities of the various professionals that manage data and information in an organization.
DAT
520
Decision Methods and Modeling
The role of many analysts is as much about interpreting the results of data analysis as it is about gathering the data and "crunching the numbers." In this course, students will learn how to evaluate data in context, interpret data trends, and receive an overview of decision support management techniques such as predictive modeling, risk assessment and optimization, and analytics algorithms, which will set the stage for more advanced study in subsequent courses. Concepts from enterprise data management, including data warehousing and business intelligence, will provide a foundation for examining the topics of data mining, advanced and dimensional data modeling, and decision support system development as techniques for an organization's competitive advantage.
DAT
530
Presentation and Visualization of Data
In addition to the gathering and interpretation of data, today's business environment calls upon the analyst to communicate the results of data analysis to a variety of audiences. In this course students will learn how to synthesize the technical components of data analysis into reports, presentations, and visual dashboards that are meaningful for the intended audience and deliver those components in a coherent, convincing format.
DAT
610
Optimization and Risk Assessment
In the competitive business world, using data to its best advantage becomes all the more crucial. In this course, students will learn how to discern the levels of relevancy of data and the impact it has on operations as well as hone their ability to identify macro and micro level risk and evaluate risk management programs, policies, and strategies.
DAT
640
Predictive Analytics
Building on prior coursework in decision methods and modeling, students will get a deeper understanding of the art and science of predictive analysis. Students will examine the elements that contribute to building reliable predictive models that result in actionable performance predictions such as identifying the variables that have the most predictive power and developing and deploying predictive models currently in use.
DAT
650
Advanced Data Analytics
This course will emphasize the employment of advanced analytic strategies over the entire life cycle of the data analysis process. Using a comprehensive case-studies approach, students will logically extend and add definition to their existing analytic skill set, resulting in the development of a project proposal that will serve as preparation for the capstone experience.
QSO
640
Project Management
This course includes the study of concepts, tools, and practices of project management. The course adopts a managerial process approach to Project Management, which consists of initiating, planning, executing, controlling and closing the project. Major topics will include project scope, project time, project cost, project quality, project risk, project resources, project communications and how to be an effective project manager. Cases are utilized to integrate the learning in the course and provide decision- making experience for the student.
DAT
690
Capstone in Data Analytics
This capstone course is the culminating experience for the M.S. in Data Analytics program. The aim of the capstone is to assess students' ability to synthesize and integrate the knowledge and skills they have developed throughout their coursework, rather than introducing new concepts. This course is structured to support student success in fulfilling program requirements.
Program Outcomes
- Conduct thorough needs assessments using statistical, analytical, and applied research techniques and consult organizational stakeholders on business requirements to offer logical and effective recommendations for data analytics initiatives
- Design and implement advanced modeling techniques, such as predictive modeling, risk-assessment and optimization, and analytics algorithms using structured and unstructured data to provide new solutions to complex organizational issues
- Communicate with professionalism, accuracy, and transparency using interactive and dynamic visualization tools to translate technical information and offer effective solutions to organizational stakeholders
- Apply effective collaborative and essential project management strategies to facilitate and improve the work of diverse and multi-functional teams, streamline processes, and lead projects to successful outputs
- Protect the integrity and privacy of data, organizations, and consumers through advanced technology solutions and ethical and legal practices in all aspects of the profession
- Employ applied, contextual knowledge of an organizations industry to target new data opportunities that improve an organizations competitiveness, effectiveness, and longevity
- Adapt and implement innovative methods, models, and technologies that allow for adaptability to new and unexpected changes and improve the agility of data analytics projects
- Position data analytics as a competitive advantage to organizations by accurately communicating the cost and benefits of data analytics projects and technologies as well as the long-term benefits of data-driven decision making
Tuition & Fees
Tuition rates for SNHU's online degree programs are among the lowest in the nation. We offer a 25% tuition discount for U.S. service members, both full and part time, and the spouses of those on active duty.
|
Online Graduate Programs
|
Per Course*
|
Per Credit Hour*
|
|
Degree/Certificates
|
$1,881 |
$627 |
Degree/Certificates
(U.S. service members, both full and part time, and the spouses of those on active duty)
|
$1,410 |
$470 |
*Tuition Rates are subject to change and are reviewed Annually.
Additional Costs:
$40 Application Fee, $150 Graduation Fee, Course Materials ($ varies by course)
University Accreditation
Southern New Hampshire University is a private, nonprofit institution accredited by the New England Commission of Higher Education as well as several other accrediting bodies. More...
*Source: Burning Glass, The Quant Crunch: How the demand for data science skills is disrupting the job market, on the Internet, at http://burning-glass.com/wp-content/uploads/The_Quant_Crunch.pdf (viewed online December 15, 2017). Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, on the Internet, at https://www.bls.gov/ooh/business-and-financial/market-research-analysts.htm (viewed online December 13, 2017). Cited projections may not reflect local and/or short-term economic or job conditions and do not guarantee actual job growth.
*The Harvard Business Review - October 2012 Edition, on the Internet at https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century (viewed online August 24, 2017).
*CareerCast - "The Best Jobs of 2017", on the Internet at http://www.careercast.com/jobs-rated/best-jobs-2017?page=4 (viewed online September 13, 2017).
*CNN Money - "Fastest Growing Jobs", on the Internet at http://money.cnn.com/gallery/pf/2017/01/05/fastest-growing-jobs-2017/2.html (viewed online September 13, 2017).
*Glassdoor - "50 Best Jobs in America", on the Internet at https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm (viewed online September 13, 2017).
*Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2016-17 Edition, on the Internet at https://www.bls.gov/ooh/business-and-financial/market-research-analysts.htm & https://www.bls.gov/ooh/math/operations-research-analysts.htm (viewed online August 2, 2017). Cited projections may not reflect local and/or short-term economic or job conditions and do not guarantee actual job growth