Success is Your Dataset with a Master's in Data Analytics
Earning a Master of Science in Data Science and Analytics is a great way to expand your career into the areas of data science and analytics, data mining, machine learning, data management, and database applications. The demand for candidates to fill data science and analytics leadership and development roles is higher than the number of qualified analysts available. Maximize your earning potential and career advancement opportunities with this data science and analytics master’s degree from WGU.
This data analytics degree program focuses on both theory and application, allowing you to “learn by doing” as you complete data science and analytics projects in stages. We use cutting-edge and highly sought-after technology to help you learn about machine learning, modern analytic tools and languages (Python, R, SQL, and Tableau), and more. Additionally, this unique program allows you to choose from a variety of datasets around industry-specific themes to completely customize your degree. Learn exactly what you want and need for your career.
70% of students finish within
WGU lets you move more quickly through material you already know and advance as soon as you're ready. The result: You may finish faster.
Tuition per six-month term is
Tuition charged per term—rather than per credit—helps you control the ultimate cost of your degree. Finish faster, pay less!
Certifications that may transfer
Your Oracle SQL Expert certification may waive course requirements.
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COURSES & COMPETENCIES
Data Analytics Courses
The WGU M.S. Data Analytics degree program was designed, and is regularly updated, with input from the experts on our Information Technology Program Council. This ensures that you learn best practices for the latest developments in data analytics.
This information technology degree program is composed of the following courses. You will typically complete them one at a time as you make your way through your program, working with your Program Mentor each term to build your personalized Degree Plan. You’ll work through each course as quickly as you can study and learn the material. As soon as you’re ready, you’ll pass the assessment, complete the course, and move on. This means you can finish as many courses as you're able in a term at no additional cost.
The M.S. Data Analytics degree program is an all-online program that you will complete through independent study with the support of WGU faculty. You will be expected to complete at least 8 competency units (WGU's equivalent of the credit hour) each 6-month term. (Each course is typically 3 or 4 units). There’s no limit on the number of units you can complete each term, so the more courses you complete, the quicker you can finish your program.
Advanced Data Analytics prepares students for career-long growth in steadily advancing tools and techniques and provides emerging concepts in data analysis. This course hones the mental and theoretical flexibility that will be required of analysts in the coming decades while grounding their approach firmly in ethical and organizational-need-focused practice. Topics include machine learning, neural networks, randomness, and unconventional data sources. Data Mining II is a prerequisite for this course.
Data Cleaning continues building proficiency in the data analytics life cycle with data preparation skills. This course addresses exploring, transforming, and imputing data as well as handling outliers. Learners write code to manipulate, structure, and clean data as well as to reduce features in data sets. The following courses are prerequisites: The Data Analytics Journey, and Data Acquisition.
Predictive Modeling builds on initial data preparation, cleaning, and analysis, enabling students to make assertions vital to organizational needs. In this course, students conduct logistic regression and multiple regression to model the phenomena revealed by data. The course covers normality, homoscedasticity, and significance, preparing students to communicate findings and the limitations of those findings accurately to organizational leaders. Exploratory Data Analysis is a prerequisite for this course.
Exploratory Data Analysis covers statistical principles supporting the data analytics life cycle. Students in this course compute and interpret measures of central tendency, correlations, and variation. The course introduces hypothesis testing, focusing on application for parametric tests, and addresses communication skills and tools to explain an analyst’s findings to others within an organization. Data Cleaning is a required prerequisite for this course.
The Data Analytics Journey gives an overview of the entire analytics life cycle. Learners gain fluency in data analytics terminology, tools, and techniques. The course contextualizes the data analytics journey firmly with organizational metrics and requirements to position graduates to answer key questions for businesses and other employers. This course has no prerequisites.
Representation and Reporting focuses on communicating observations and patterns to diverse stakeholders, a key aspect of the data analytics life cycle. This course helps students gain communication and storytelling skills. It also covers data visualizations, audio representations, and interactive dashboards. The prerequisite for this course is Data Mining I.
Data Mining II adds vital tools to data analytics arsenal that incorporates unsupervised models. This course explains when, how, and why to use these tools to best meet organizational needs. The prerequisite for this course is Advanced Data Acquisition.
Data Mining I expands predictive modeling into nonlinear dimensions, enhancing the capabilities and effectiveness of the data analytics lifecycle. In this course, learners implement supervised models—specifically classification and prediction data mining models—to unearth relationships among variables that are not apparent with more surface-level techniques. The course provides frameworks for assessing models’ sensitivity and specificity. D208 Predictive Modeling is a prerequisite to this course.
Data Acquisition builds proficiency in Structured Query Language (SQL) and the initial stages of the data analytics lifecycle. The course introduces relational databases. Students gain concrete skills in data transference and database manipulation. There are no prerequisites.
Advanced Data Acquisition enhances theoretical and SQL skills in furthering the data analytics life cycle. This course covers advanced SQL operations, aggregating data, and acquiring data from various sources in support of core organizational needs. The prerequisite for this course is Representation and Reporting.
The Data Analytics Graduate Capstone allows students to apply the academic and professional abilities developed as a graduate student. This capstone challenges students to integrate skills and knowledge from several program domains into one project. Advanced Data Analytics is a prerequisite for this course.
Program consists of 11 courses
At WGU, we design our curriculum to be timely, relevant, and practical—all to ensure your degree is proof you really know your stuff.
Special requirements for this program
At the end of your program, you will complete a capstone project that represents the culmination of all your hard work—this project consists of a technical work proposal, the proposal’s implementation, and a post-implementation report that describes the graduate’s experience.
According to a 2021 Harris Poll, just two years after graduation, WGU grads report earning $18,200 more per year, and that amount increases to $25,900 four years after graduation.
On Your Schedule
No class times, no assignment deadlines. You are in charge of your learning and schedule. You can move through your courses as quickly as you master the material, meaning you can graduate faster.
The data analytics bachelor's degree at WGU is 100% online, which means it works wherever you are. You can do your coursework at night after working at your full-time job, on weekends, while you're traveling the world or on vacation—it's entirely up to you.
One important measure of a degree’s value is the reputation of the university where it was earned. When employers, industry leaders, and academic experts hold your alma mater in high esteem, you reap the benefits of that respect. WGU is a pioneer in reinventing higher education for the 21st century, and our quality has been recognized.
Relevant Data Analytics Certificates Included in this Degree
WGU certificates you will be positioned to earn in this degree program include Data Preparation, Data Analytics Fundamentals, and Advanced Data Modeling. Earning certificates on the path to your degree gives you the knowledge, skills, and credentials that will immediately boost your résumé—even before you complete your degree program.
- Advanced Data Modeling
COST & TIME
An Affordable Online Data Analytics Degree
By charging per six-month term rather than per credit—and empowering students to accelerate through material they know well or learn quickly—WGU helps students control the ultimate cost of their degrees. The faster you complete your program, the less you pay for your degree.
A College Degree Within Reach
There is help available to make paying for school possible for you:
Designed for Professionals with Tech Talent, Competency-Based Education Puts You in the Driver’s Seat of Your Data Analytics Degree
With WGU, you can earn while you learn. Our unique education model means you can continue to work full-time while you're earning your degree. Continue to make money while enhancing your career offering with the help of a master's degree in data analytics. Nothing is in your way when you choose WGU—our unique education model lets you move through courses as soon as you can master the material. You can graduate faster and boost your résumé sooner.
Set Goals. Get Results. Data Leadership Careers Start With a Master's Degree in Data Analytics
When properly analyzed, every transaction—commercial, medical, social, or academic—can help lead to better business decisions and outcomes in your industry. And as the amount of data rapidly increases, so does the need for qualified data analytics leaders.
Our economy runs on data, and the amount of data we use is growing at an unprecedented rate. Every industry from advertising to zoology is going digital, and almost all organizations need experts who can maximize that data. When you have completed your data analytics degree program online, your skills will already be in high demand. The knowledge and techniques you’ll gain as you complete your degree will provide you with all the tools necessary for a for a successful career.
Return on Your Investment
Learn About All the Job Opportunities in Data Analytics
Students who earn a master’s degree in data analytics will be prepared to maximize leadership opportunities in careers including:
- Data Analyst
- Data Administrator
- Business Analyst
- Data Engineer
- Business Intelligence Analyst
- Information Research Scientist
- Advanced Analytics Expert
WGU Grads Hold Positions With Top Employers
Data Analytics Admissions Requirements
To be considered for enrollment in this program, you must:
1. Possess a bachelor’s degree in a STEM field, Business degree (Quantitative Analysis, Accounting, Economics, Finance, or degree with similar quantitative focus).
2. Possess any bachelor’s degree PLUS one of the following:
- Two years of related work experience
- Relevant and current IT certification
- Related IT coursework
NOTE: You do not need to take the GRE or GMAT to be admitted to this program. Learn why we don't require these tests.
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FAQs about Master's in Data Analytics Programs
- General IT Program Questions
- Master in Data Analytics Questions
You should speak with an Enrollment Counselor. WGU can often provide advice or resources to help a prospective student fulfill enrollment prerequisites.
When you enroll in a WGU degree program, our goal is to see you through to graduation. Admission requirements are designed to increase your likelihood of success. Years of data and experience with the nontraditional students WGU serves have shown us how various types of academic and professional experience can be highly important in helping a student persist to graduation. Industry certifications are one of many ways a student can meet eligibility.
WGU has an obligation to our graduates—and their current and future employers—to ensure WGU alumni have mastered the most up-to-date, current competencies and skills needed in the workplace. Recency of certifications helps us ensure that students have demonstrated competency in skills as they are needed in today's working world.
As a full-time student, you will be required to maintain a minimum pace of 12 competency units (CUs) per term for undergraduate programs or 8 CUs per term for graduate programs. However, there is no maximum speed—once you complete a course, you move immediately to the next, and you complete a course not by waiting for the syllabus, the professor, or the rest of the class. You progress by learning the material and proving it—so you can move through your coursework at the speed of your own learning and experience.
Instructors are highly educated, experienced experts in the subject matter of a course. Unlike in a traditional university where going to class means listening to an instructor lecture while you take notes and try to learn in a group setting, WGU's Instructors provide one-on-one instruction and support when you need it—tailoring the instruction to your precise needs when you need it. Instructors also provide additional resources, lead topical discussions in online communities, and find countless other ways to bring a specific course to life for students.
Absolutely. Data makes our world go round, and every business in every industry needs data to help make decisions. You can work in any field with the help of a degree in data analytics. A master's in data analytics will prepare you to convert raw data into meaningful information that can help business leaders make decisions. Become a great influence with the help of an master's degree in data analytics.
An MS in data analytics is a Master of Science in Data Analytics. This degree helps students learn how to do the many tasks associated with taking raw data and turning it into meaningful information. This includes data mining, programming, analyzation, and more.
A master's degree in data science or data analytics is a great option for IT professionals who are looking to take their career to the next level. Experience in the IT field will be extremely helpful as you pursue a master's degree in data analytics. If you're looking to start a career in IT, a bachelor's degree or certifications can help you begin.
Common careers for those with a master's degree in data analytics include:
- Data analyst
- Business analyst
- Data engineer
- Business intelligence analyst
- Information research scientist
- Advanced analytics expert
A master's degree in data science or data analytics can be challenging, but if you have a solid background and understanding in IT, you'll be able to excel. Experience, education, and certifications in IT can help you be better prepared for this master's degree.
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