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 Bachelor of Science 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 mathematicians and statisticians tops the list at 33% growth through 2026.* The need for operations research analysts is projected at 27%, and market research analyst growth is projected to see 23% growth.*
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.
MAT 136 - Introduction to Quantitative Analysis, MAT 140 - Precalculus and MAT 243 - Applied Statistics for Science, Technology, Engineering, and Mathematics (STEM) are dictated courses for the General Education Program.
New students are eligible to take a free math assessment that, depending on their score, can earn them up to six math credits toward their degree, saving time and money. Learn more today.
SNHU's bachelor's in data analytics program includes:
General Education Program
Our programs are designed to equip you with the skills and insights you need to move forward. In recent years, employers have stressed the need for graduates with higher order skills - the skills that go beyond technical knowledge - such as:
All bachelor's students are required to take general education classes. Through foundation, exploration and integration courses, students learn to think critically, creatively and collaboratively, giving you the edge employers are looking for.
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.
This is a second course in statistics that builds upon knowledge gained in an introduction to 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.
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.
Learn how to apply a comprehensive approach to data analytics in the solving of business problems by building upon the principles set forth in DAT 210. Evaluate the tools and resources available in terms of their appropriateness to complex business scenarios. Explore the collaborative nature of data analytics projects and the necessity for coordination across projects through conducting an initial data analytics project and creating a collaborative report of 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 capstone course is the culminating experience for the B.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.
Learn the fundamentals of programming concepts including data types, variables, decision statements, loops, input and output. Develop simple scripts using common scripting language constructs including lists, literals, and regular expressions. Gain an introduction to programming through hands-on activities that are beginner-friendly.
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.
Develop database designs using industry-standard modelling tools and techniques. Evaluate user requirements to identify optimal database models that solve common business problems. Examine approaches to structural and object-orient design that consider today's varied data types.
Employ project management strategies specific to IT projects. Examine responsibilities of key stakeholders. Explain project planning with key considerations related to risk management and project tracking.
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.
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% tuition discount for U.S. service members, both full and part time, and the spouses of those on active duty.
*Tuition Rates are subject to change and are reviewed annually.
No Application Fee, $150 Graduation Fee, Course Materials ($ varies by course)
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...