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For businesses, government agencies, the military and nonprofit organizations, the wealth of geospatial data out there is a game changer. This information gathered from geographic information systems (GIS), GPS, satellites, social media, location sensors and mobile devices offers complex insight into human behavior, population shifts, weather patterns and a region’s current and historical characteristics. While geospatial information has existed in some form since the 1960s, the field of data science and analytics has transformed the information available and how it’s used to develop visualizations, monitor trends and shape decisions.
Pursue this growing discipline with an online master of science in data science and analytics with an emphasis in geospatial analytics from the University of Missouri (Mizzou). Our program attracts individuals from diverse backgrounds interested in the principles, tools and applications of data science and analytics who are looking to gain hands-on experience and enhance their careers.
Core courses provide a comprehensive introduction to data science and analytics’ mathematical foundation, tools, languages and privacy considerations. The emphasis area then highlights real-world use and data science’s role in assessing geospatial information. Thinking about your career growth, you’ll apply what you’ve learned in a capstone project. Here, you’ll analyze and draw insights from a large data set while receiving guidance from industry leaders and Mizzou’s renowned faculty.
Explore other emphasis areas from Mizzou's master of science in data science and analytics:
Quick facts
Official name
Master of science in data science and analytics with an emphasis in geospatial analyticsCampus
Program type
Master's degreeAcademic home
Graduate School | MU Institute for Data Science and InformaticsDelivery mode
100% onlineAccreditation
Higher Learning CommissionCredit hours
34Estimated cost
$35,094.80*This cost is for illustrative purposes only. Your hours and costs will differ, depending on your transfer hours, your course choices and your academic progress. See more about tuition and financial aid.
Why earn a master’s degree in geospatial analytics?
Location-based data influences several industries and developments in the present, from tracking weather and population trends to learning more about customers within a geographic area to overseeing urban planning and infrastructure efforts. Surveying and the use of GIS shaped these industries for decades. Today, geospatial analytics streamlines these data-gathering and interpretation processes and allows for an increasingly granular level of information.
As a discipline, geospatial analytics involves compiling data from across multiple spatial and nonspatial sources, analyzing and manipulating the information available to identify patterns and creating visualizations in the form of maps, graphics and cartograms. Visualizations may focus strictly on the landscape and an area’s geographic features, may examine people and their habits over a region or may consider historical shifts, especially in relation to current events. Our program was ranked No. 9 by Fortune.com for "Best Online Master's in Data Science Programs in 2023". This underscores Mizzou's mission to meet the high demand for training today's top data science professionals.
To enhance your knowledge of geospatial analytics’ technologies and applications, the online master’s in data science and analytics:
- Takes a multidisciplinary approach to expand your understanding of big data and its influence on geospatial analytics, from statistical analysis to database system management, information retrieval, data mining and machine learning
- Introduces you to tools and techniques used across all data science applications, with focus given to the structure and analysis of spatial data
- Helps you start to think about data analytics as an integral decision-making tool, including for identifying consumer and geographic patterns
- Touches on current trends in data science and analytics and how they continue to shape the use of geospatial information, including issues you’ll counter with digital imagery, thermal imaging and microwave remote sensing
- Instructs you in acquiring and analyzing large data sets and communicating your findings through visualizations, from using geospatial and remote sensing data stored in several formats to managing, accessing and manipulating this information
- Goes over ethics and security for protecting data collections potentially containing sensitive information
- Integrates hands-on learning right from the beginning to improve your familiarity of data analysis tools and techniques
- Covers the key concepts and techniques of remote sensing, including spatial and spectral characteristics for passive, active, thermal and other phenomenologies
Career prospects
Enhance the skills you bring as a cartographer or geoscientist, both predicted to see steady growth between 2020 and 2030.
Beyond these two fields, this online master’s in geospatial data science and analytics prepares you to identify, monitor and communicate geographic and population patterns in telecommunications, urban development, agriculture, the military, natural resources, transportation, logistics, meteorology, energy industry and business. Possible job titles include:
- Geospatial information scientist
- Geospatial asset manager
- Geospatial analytics engineer
- Geospatial technician
Program structure
As you begin the online master’s in data science and analytics, you’ll start with a rigorous 19 credit-hour core before proceeding onto the concentrated focus of the geospatial analytics emphasis area (nine credit hours). You’ll then get additional hands-on experience through a case study (three credit hours) and a capstone project (three credit hours).
All courses are held online in eight-week modules using a semester structure, allowing you to complete the program in about two years. Additionally, you have the opportunity to attend an optional, on-campus Data Science Week in the spring, where you can collaborate with and gain real-world insights from our faculty members and partnering industry professionals.
During the core sequence, you’ll develop a strong foundation in all data science and analytics principles, including its statistical formulas and methods for accessing, cleansing, modeling, analyzing and visualizing data. You’ll further learn about the design, management and function of database systems, ethics for various industries and settings, data collection and storage security and applied machine learning and modeling.
As the culmination of the online master’s in data science and analytics program, you’ll participate in an eight-week group case study during the summer semester. This session paves the way in terms of practice and reinforcement for your capstone project.
Geospatial analytics courses
From the core, you’ll take three emphasis area courses covering:
- Spatial and geostatistical analysis, including common concerns with using, implementing and assessing spatial data
- Theoretical and practical issues involved in geospatial data engineering, including access, indexing, retrieval, storage, management and its place in the full data science lifecycle
- Remote sensing data analytics and information extraction, with emphasis on raster data sets and processing
Delivery
100% onlineCalendar system
Semester-basedTypical program length
2 yearsAccreditation
The University of Missouri is accredited by the Higher Learning Commission, one of six regional institutional accreditors in the United States.
Faculty spotlight
Chi-Ren Shyu has organized and chaired technical program committees for several Institute of Electrical and Electronics Engineers (IEEE) conferences, such as IEEE HealthCom, IEEE BigMM, IEEE BIBM and more. He represents the University of Missouri (Mizzou) serving on the Southeast Conference (SEC) Artificial Intelligence Curriculum Consortium. Since joining Mizzou in 2000, Shyu has received the National Science Foundation CAREER award, Engineering Faculty Research Award, Engineering Teaching Excellence Award and more. His current research focuses on digital health, explainable AI, quantum computing and spatial big data analytics. He is a Fellow of the American Medical Informatics Association.