MS in Data Analytics - Curriculum

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Meet the Demands of the Complex World
of Big Data

A study by IDC and EMC predicts that by the year 2020, the size of the digital universe will reach 40 trillion gigabytes. In just one decade, the amount of digital data produced worldwide is projected to increase 30 times. Organizations are expected to be able to handle and leverage the volume, velocity and variety of this new data in real-time. Southern New Hampshire University’s 36-credit master's degree in Data Analytics was specially developed to arm data scientists, analysts and other data professionals with the skills to tackle this unprecedented and unwavering growth.

MS in Data Analytics Learning Outcomes

Students taking our MS in data analytics courses will be prepared to be a strategic asset to any organization by making data a strategic part of critical decision-making. Courses in SNHU’s master's degree in data analytics programs will enable graduates to:

  • Offer logical and effective recommendations for data analytics initiatives by consulting organizational stakeholders on business requirements and by conducting thorough needs assessments using statistical, analytical and applied research techniques
  • Provide new solutions to complex organizational issues through the design and implementation of advanced modeling techniques, such as predictive modeling, risk-assessment and optimization, and analytics algorithms using structured and unstructured data
  • Communicate to organizational stakeholders with professionalism, accuracy and transparency using interactive and dynamic visualization tools to translate technical information
  • Apply effective collaborative and project management strategies to facilitate and improve the work of diverse and multifunctional teams, streamline processes and lead projects to successful outcomes
  • 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
  • Target new data opportunities that improve an organization’s competitiveness, effectiveness and longevity by employing applied, contextual industry knowledge
  • Adapt and implement innovative methods, models and technologies that allow for flexibility 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

MS in Data Analytics Required Courses

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-510 and DAT-520
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.
DAT-510, DAT-520, and DAT-640
DAT-690: Capstone in Data Analytics
This capstone course integrates previous coursework and practical experience with a focus on authentic demonstration of competencies outlined by the program. Rather than introducing new concepts, students will synthesize prior learning to design, develop, and execute an analytics project on their chosen subject as a culmination of their studies. The course will be structured around this critical capstone assessment, so that students have the appropriate support and resources required to be successful. Prerequisites: 27 credits. It is required that students complete DAT-650 before enrolling in this course.
DAT-650 and completed 27 credits
QSO-500: Business Research
This course presents an overview of the various primary and secondary research methodologies used in the business world and the application of statistical techniques to those strategies. The focus of this course is the design and execution of a practical, primary research. It is recommended that this course be one of the first three taken in degree programs in which it is required. Background preparation: 3 credit hours in statistics.
QSO-510: Quantitative Analysis for Decision Making
This is a survey of the mathematical, probabilistic and statistical tools available for assisting in the operation and management of industrial organizations. Background preparation: 6 credit hours in mathematics and 3 credit hours in statistics, or the equivalent.
QSO-520: Management Science through Spreadsheets
This is an application-oriented course that will provide students with a working knowledge of the most commonly used Management Science/Operations Research techniques such as linear programming, integer programming, goal programming, nonlinear programming, network modeling, queuing theory and simulation. The students will learn how to combine the power of the management science and spreadsheets to model and solve a wide variety of business problems.
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.


For those who do not meet the minimum admission requirements, the following courses may be required:

DAT-500: Data and Information Management
This course provides students with an introduction to key concepts and tools in data and information management. Basic database administration tasks, file processing, file organization, data storage, and conceptual, logical, and physical data models will be introduced as a foundation to advanced database, data analysis, and information management skills. Students will gain exposure and be able to differentiate among common data and information management technologies that provide decision support capabilities to organizations.
MBA-501: Mathematics and Statistics for Business
This is an applied course, which will provide students with the mathematical knowledge and skills that underlie many courses offered in the school of business. Students will learn the fundamental concepts and methods of linear algebra, mathematical functions, differential calculus and statistics and their applications to business. They will also sharpen their quantitative, analytical and problem-solving skills that are so important for success in the world of business today.
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