The most successful businesses employ professionals to analyze data and find more efficient ways to operate. The master’s in data analytics online program at SNHU can help you gain specialized skills in data analytics to fill this role.
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. PSM graduates are prepared to assume high-level careers with science/technology-based employers.
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. Upon completion of the capstone in data analytics, you’ll come away knowing how to leverage big 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:
The future of business depends on harnessing big data – in all its myriad unstructured formats and disparate sources – faster than the competition, and then using it to make better, more consistent and more fact-based decisions. But there’s a talent gap for data analysts with the specialized skills and broad-based knowledge to meet this growing demand. The U.S. Bureau of Labor Statistics projects demand for market research analysts at 32 percent and operations research analysts at 27 percent through 2022.
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.
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, its impact on the business world, and the career options that may be available as a result. Emphasis will be placed upon the verification of data, the role of regulatory organizations, and the privacy and ethics issues that surround its use.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Tuition rates for SNHU's online degree programs are among the lowest in the nation. We offer a 30 percent tuition discount for active-duty service members and their spouses.
Application Fee ($40), Graduation Fee ($150), Books (course-by-course)
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