Data analysis applies to a world that goes beyond business decisions – information influences every aspect of our lives. Engineering, architecture, pharmacology and more all depend on data to make critical decisions that affect millions of people every day.
As businesses become smarter, more efficient and savvier at predicting future opportunities and risks through data analytics, the need for professionals in this field continues to rise – and with it, the value of a BS in Data Analytics. Southern New Hampshire University's data analytics degree online program will position you to capitalize on this critical and unprecedented demand.
The undergraduate data analytics degree online combines facets of business, information technology and mathematics with data mining, simulation and optimization. With this broad range of knowledge, bachelor’s in data analytics students learn not only to dissect information, but also to put it in context of the challenges that face the world today. Your in-depth coursework in the SNHU data analytics degree program will increase your understanding and develop your information analysis expertise. Upon earning your BS in Data Analytics, you'll be able to:
As a private, nonprofit university, SNHU has one mission – to help you see yourself succeed. The benefits of earning your bachelor’s in data analytics at SNHU include:
Upon completion of the data analytics degree online bachelor’s program, you can explore a wide range of career options across public, private and nonprofit sectors, including market researcher, statistician, data miner, analyst and information technology specialist. According to the U.S. Bureau of Labor Statistics, demand for market research analysts tops the list at 32 percent growth. Demand for operations research analysts and statisticians is projected at 27 percent, with demand for IT specialists close behind at 17 percent.
The curriculum for SNHU’s undergraduate data analytics degree is designed around the onslaught of data that organizations face every day. The bachelor’s in data analytics coursework combines data mining and structure with modeling and communication to build a broad and thorough education that will serve you well throughout your career. In addition, students can elect to learn SAS or SQL modeling techniques.
Calculus is the mathematical study of change that has widespread applications in science, engineering, economics and business. This course provides a rigorous introduction to single-variable calculus. Topics include limits, continuity, differentiation and integration of algebraic, trigonometric, exponential, and logarithmic functions, applications of derivatives, and integration, including the Fundamental Theorem of Calculus. This course will encourage students to think beyond memorizing formulas and to work towards understanding concepts. Students may not take both MAT 210 and MAT 225 for credit.
This is a second course in statistics that builds upon knowledge gained in MAT 240 or an AP statistics course. Students will learn to build statistical models and implement regression analysis in real-world problems from engineering, sociology, psychology, science, and business. Topics include multiple regression models (including first-order, second-order and interaction models with quantitative and qualitative variables), regression pitfalls, and residual analysis. Students will gain experience not only in the mechanics of regression analysis (often by means of a statistical software package) but also in deciding on appropriate models, selecting inferential techniques to answer a particular question, interpreting results, and diagnosing problems.
This course is an introduction to the design, implementation, and understanding of computer programs. The course emphasizes programming as a problem-solving technique in business and engineering applications. Students will write computer code in a logical, structured, and organized manner. The course also covers the key concepts of object orientation, including inheritance, encapsulation, polymorphism and communication with messages. Other topics include classes and objects, base classes and class hierarchies, abstract and concrete classes. Students will learn to write, review and document interactive applications and working with Software Development Kits and Integrated Development Environment tools. Offered every year. This is a programming course and lab intense. Prerequisite or Concurrent: IT 100
Select one of the following:
The SAS programming suite of products is commonly used throughout the industry for making sense of the vast amount of data that is available today and for turning that data into actionable items for an organization. Through the creation of SAS programs of varying complexity, students will solve common data analysis problems and learn the general programming conventions of SAS along with the data management and reporting utilities of the basic SAS product. This course will also provide students with an overview of the wide array of SAS data analytics products and their use within various industries.
Structured Query Language (SQL) is at the heart of most data systems. In this course, students will learn the basics of SQL programming as it relates to both database management and data manipulation. This course will also provide students with an overview of more advanced topics such as embedded SQL, function calls, and stored procedures.
This course covers the use of SQL within an Oracle Database Environment. Students will learn to retrieve, restrict, sort, report, and display data using SQL statements. Topics also include writing sub-queries, manipulating data, creating and managing tables, and working with schema objects. Students will gain hands-on experience in functional Oracle database environment.
The emergence of new data sources is transforming the role of the data analyst from one who simply reports information to one who is charged with making sense of the available data and distilling from it the salient aspects for the given audience. In this course, students will examine the concepts of data analysis and how it informs the business process. Emphasis will be placed on the development of sound research questions, the identification and verification of data sources, the retrieval, cleaning, and manipulation of data, and the process for identifying the data elements that are relevant for a given audience. An overview of the regulatory organizations that govern the release of data will also be reviewed.
A large portion of data analytics focuses on identifying meaningful patterns in data. Using a case studies approach, students will examine effective strategies that blend both hypothesis testing and data-driven discovery methods to identify meaningful data patterns and apply that knowledge to common business problems. Emphasis will be placed on data-mining tasks such as classification, clustering, and sequential pattern discovery.
Building upon the principles set forth in DAT 210, students will begin to develop a comprehensive approach to the application of data analytics in the solving of business problems. In this course, students will evaluate the tools and resources available in terms of their appropriateness to complex business scenarios. This course will highlight the collaborative nature of data analytics projects and the necessity for coordination across projects. Students will conduct an initial data analytics project and create a collaborative report of their findings.
Building upon the principles set forth in prior coursework, students will engage in a comprehensive approach to the application of data analytics in the solving of business problems employing the techniques frequently used in the discipline. Emphasis will be placed on the different types of forecasting techniques such as sales, risk, retention, and attrition as applied to a variety of industries
In order for data analytics to be effective, reports and findings must be presented in a manner that is relevant to one's audience. In this course students will hone their technical writing and presentation skills to engage individuals at all levels throughout an organization. Ethics, security, and privacy considerations as they relate to reporting will also be discussed.
This course represents the integration of previous coursework and practical experience with a focus on authentic demonstration of competencies outlined by the program. Students will present a portfolio containing selections of prior coursework combined with metacognitive reflection and the development of a professional statement of purpose as the culmination of their studies. The course will be structured around this critical task, so that students have the appropriate support and resources required to be successful.
This course provides students with an introduction to the foundations of data and information management, centered around the core skills of data management and database organization. The course will focus on identifying organizational requirements for data and information, modeling the requirements using relational techniques, implementing the models into a database using a database management system, and understanding the issues of data quality and data security. The course will also introduce the framework of enterprise information management and the growing need for managing data and information in organizations effectively to support decision making and competitive advantage.
This course covers project management strategies specific to IT projects. These project management strategies include: project initiation, scope definition, planning, execution, control, coordination, closure acceptance, and support.
This course covers the design and implementation of information systems within a database management system environment. Students will demonstrate their mastery of the design process acquired in earlier courses by designing and constructing a physical system using database software to implement logical design. Topics include data models and modeling tools and techniques; approaches to structural and object design; models for databases (relational, hierarchical, networked and object-oriented designs) CASE tools, data dictionaries, repositories and warehouses, Windows/GUI coding and/or implementation, code and application generation, client-server planning, testing and installation, system conversion, end-user training and integration and post-implementation review. Offered every year.
This course introduces the student to mathematical techniques that may be used to aid decision-making. Topics may include linear programming, PERT, CPM, network analysis and others. Offered once a year.
Elective Courses: 9 Credits
DAD, IT, or QSO - three (3) Database Administration, Information Technology, or Quantitative Studies/Operations Management courses at the 200-level or higher
Free Elective Credits: 24
Total Credits: 120
Tuition rates for SNHU's online degree programs are among the lowest in the nation. We offer financial aid packages to those who qualify, plus a 30 percent tuition discount for active-duty service members and their spouses.
*Tuition rates are subject to change. Changes are generally implemented in June each year.
Additional Costs Books (course by course).
Students are responsible for providing their own internet access.
Southern New Hampshire University is a private, nonprofit institution accredited by the New England Association of Schools and Colleges as well as several other accrediting bodies. More...