Master of Science in Data Analytics

Become an in-demand data analytics professional

Master of Science - Data Analytics (30 credits)

Cultivate the skills and knowledge for in-demand data analytics careers through the master in data analytics at Davenport University. This 30-credit master’s degree is offered fully online through Davenport’s pioneering Global Campus and is available to those with or without data backgrounds.

Through Davenport’s master in data analytics online, you’ll develop expertise in data mining, data visualization and storytelling, cloud computing, predictive analysis and data warehousing. Gain a command of industry software, such as SQL, R Programming, IBM SPSS Statistics, IBM SPSS Modeler, Tableau and Rstudio.

Davenport’s courses align with the Quality Matters (QM) rubric to ensure you’re receiving a high-quality online education.

What is data analytics?

Data analytics involves using tools and techniques to turn raw data into insights that help companies and organizations make better business decisions. The need for highly knowledgeable and skilled data scientists and data analysts is skyrocketing as more and more companies adopt big data and analytics technologies. With the fully online master in data analytics at Davenport, you’ll be prepared to help businesses and organizations use data analytics to grow opportunities, reduce inefficiencies and improve outcomes.

Explore classes for Davenport’s master in data analytics

Cover all the key areas of data analytics in just 30 credits through Davenport’s master in data analytics online. To ensure you’re ready to rise to the top of the job market, our career-centered curriculum includes courses in data mining, predictive analysis, data visualization and communication and R programming. With 100% online courses you’ll enjoy the flexibility you need as a working professional to balance your data analytics degree with your life.

See Full Course List

Core Courses		12 Credits
DATA610	Essentials of Bus Analytics Essentials of big data and data analytics are introduced and include descriptive, predictive and prescriptive statistics, regression analysis, optimization techniques and data visualization. The instructional approach in this course focuses on application-based reinforcement of concepts to include the use of simulations. A key component of instruction is an emphasis on analytical report writing and other ways to effectively present data analytic results. Techniques examined emphasize applicability in multiple organizational sectors to include business, finance, human resources, healthcare, manufacturing, sport management, social services, education, non-profit, and government entities. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.	3
DATA625	Data Mining This course introduces students to data mining methods and applications. It covers basic concepts and tools for data mining, including data sources, data cleaning tools and methods, mainstream algorithms for data mining, statistical modeling, popular tools for mining structured data and unstructured data. Students will also learn how data mining can be effectively used in various application areas to drive decisions and actions. Students get hands-on practice by conducting a data analytics project using real world data sets.	3
DATA667	Data Visualization & Commnctn Data visualization and communication skills are taught using industry standard software. The instructional approach in this course focuses on application using hands-on projects to create reports and dashboards with high-impact visualizations of common data analyses to help in decision making. A key element of instruction is an emphasis on communicating the practical implications of data analytics results to a non-technical audience in a timely manner. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.	3
DATA710	R Programming R programming language concepts are covered within the context of how they are implemented in practice when conducting high-level statistical analysis. The instructional approach in this course focuses on application-based programming concepts such as reading data into R, accessing analysis tool boxes in R, writing R functions, debugging, and organizing and commenting in R code. Data mining and analysis projects will be used to provide working examples. Upon completing this course, students will be able to employ advanced modeling techniques to write R code to conduct data analysis with strong reusability.	3

Advanced Courses		15 Credits
DATA728	Advanced Data Mining This course will be a more advanced treatment of data mining and predictive analytics concepts introduced in DATA625 with a focus on customer relationship management (CRM). Using customized variations of the industry-standard CRISP-DM methodology, it will provide an experiential learning opportunity to explore all six phases of the model. This includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Industry standard tools and techniques are utilized to prepare students with the knowledge to be successful in current organizations. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA625	3
DATA742	Data Warehousing & Lakes Students will be introduced to the concept of the data warehouse and the role it plays in an organization’s overall business intelligence and analytics strategy. This course will cover the two predominate warehouse design strategies, as well as hybrid designs that combine best practices from both areas, including the requirements of a data warehouse, selecting the proper design strategy, choosing the proper tools to support that design, selecting metrics for monitoring performance, data quality, and planning future enhancements. Students will be able to build a high-level plan for implementing a data warehouse in their organization or planning future changes to an existing warehouse if present. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees.	3
DATA758 or DATA790	Essentials of Cloud Computing or Data Analytics Internship DATA758 Essentials of Cloud Computing This course introduces the essentials of cloud computing and various service models including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). These cloud service models are also reviewed in terms of their role in delivering on-demand computing resources to customers. The risks and benefits of cloud deployment models as public, private, hybrid, and community, are discussed together with the underlying infrastructure and operational considerations related to security and privacy. In addition, various cloud vendor platforms are explored to learn how cloud computing is implemented in practice. DATA790 Data Analytics Internship Contact Regional Internship Manager at least 1 semester prior to enrolling. In this course, the student integrates data analytics skills acquired through classroom instruction with on-the-job learning via work experience. Emphasis is placed on extensive hands-on experience in one or more of the following focus areas: organizing and exploring data, building dashboards, mining data, or conducting predictive analysis using industry standard software. Further, to ensure adequate practice, a minimum of 150 hours of career related work are required at the internship site as well as weekly progress reports, a written internship report and an oral presentation. Note: Any unexcused non-attendance or dismissal from an internship, practicum, clinical or fieldwork experience will result in a grade of F. A grade of B or better is required in order to earn a passing grade in this course. A criminal background check and drug screening may be required by the internship site. Additional course fee(s) apply. Prerequisite(s): DATA610, DATA667, DATA710, DATA728	3
DATA772	Stat Analysis Data Analytics This course covers statistical procedures used in data analytics with emphasis on hands-on practice. Industry standard software is used to import and prepare data for model development as well as for developing various types of regression models. Assessment of model performance and methods for model selection are also covered. Emphasis is also placed on parameter estimation, variable selection, and diagnostic checking of these models and their use for statistical inference and prediction. Both numerical and graphical techniques are used for diagnostics and reporting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA710	3
DATA785	Predictive Modeling This course covers statistical modeling in the use of statistical methods to develop models that can be used for predicting future numerical or categorical outcomes in processes for disciplines ranging from business to science. The philosophy of modeling as well as common modeling methods and model adequacy assessment procedures are covered. Industry standard software is used to prepare data, develop and assess models, obtain predictions, and present results. The main thrust of the course is on the application of predictive modeling rather than the theory behind it. Selected projects will be used to provide hands-on experience with the various steps involved in modeling and predicting. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): DATA772	3

Capstone Project		3 Credits
DATA792	Data Analytics Capstone Students will apply all of their theoretical and practical experience to design and execute an analytics project on a chosen topic as a culmination of their analytics program, thereby demonstrating competency of program learning outcomes. Students will select the techniques to be used in the study, collect and analyze data for the purpose of drawing conclusions and making recommendations to the decision makers of an organization. Note: A grade of B or better must be earned to pass this course successfully. Applicable Course Fees can be found at https://my.davenport.edu/financial-aid/how-much-does-du-cost/tuition-and-fees. Prerequisite(s): Course may only be elected in the final semester of the program.	3

Which class should I take? When should I take it?

See our Recommended Program Sequences:

22%

22% related employment growth projected through 2030

$141,817

National average annual salary for related careers

10,000+

Job openings for data scientists in 2022

30 credits vs traditional 36 saves you time and money

Why study data analytics at Davenport University?

Through the master in data analytics, you’ll learn from expert data analytics faculty who are industry-experienced data analysts and scientists. They’ll go beyond teaching you technical skills in data analytics to preparing you to communicate data analytics to nontechnical audiences. You’ll receive in-depth, hands-on practice with real-world projects in data analytics — even online. If you’re looking for something a little quicker, Davenport also offers three 12-credit data analytics certifications. You can apply certificate credits directly to the full master in data analytics.

Experience the Davenport difference:

Flexible online master’s

It’s easy to manage your data analyst master’s with your busy life. Take two online courses over 15-week semesters and finish in just 2.5 years.

Leading data analytics degree

Earn your master in data analytics from the largest online data analytics program in the state of Michigan.

96% rate of employment

Become an in-demand data scientist with 96% of Davenport grads employed within six months of graduating

Individual with dotted path line to destination

Purposefully designed curriculum

Develop expertise in three major areas of data analytics: predictive analysis, data mining and data visualization and communication

No background required

Enroll in the data analytics master’s program — with or without a data analytics background. No GRE or GMAT necessary.

Endless career opportunities

Prepare for a wide range of careers, including data manager, data analyst, consultant, business analyst, and market analyst. Graduates of Davenport’s data analytics master’s program work for top employers such as Fifth Third Bank, State of Michigan, Farmers Insurance, Spectrum Health and Steelcase.

Get started on your Master of Science in Data Analytics

Explore the admissions requirements and then take the next step toward earning your master in data analytics online.

Talk to an admissions advisor

Davenport’s admissions team is here to answer your questions. Please call us at 800.686.1600 or email us at info@davenport.edu.

Apply now and request more information

Start on the road to a successful career in data analytics. Request more information or begin your application now.

Admission Requirements

Interested students must display an undergraduate GPA of 2.75 or higher or a graduate GPA of 3.0 or higher. Plus, individuals must have a bachelor's degree with strong quantitative and analytical skills.