MSDADE · Current · 32 CUs
Master of Science, Data Analytics - Data Engineering
Source: WGU Program Guide·v202408·5/15/24
About This Degree
WGU Catalog 2026-03The MS Data Analytics degree prepares a diverse range of professionals for thriving careers in the dynamic field of data analytics. By arming graduates with the competencies needed to tackle business challenges through data mining, predictive analysis, analytics deployment, and compelling data storytelling techniques, the MSDA ensures they are well-prepared for success. Emphasizing both theory and practical application, the curriculum fosters the development of skills necessary to drive impactful change within organizations spanning various industries and sectors. The Data Engineering concentration builds upon core techniques in data management and governance to further bolster analytics initiatives, delving into cloud-native databases, data processing, and approaches to support scale. The program includes a concentration-specific capstone, providing an opportunity for students to showcase their skills in a comprehensive manner.
Official catalog text — WGU-authored.
Degree History
First offered2024-06StatusCurrentCUs32
Program Learning Outcomes
WGU Catalog 2026-03Official WGU-authored outcomes from the catalog Program Outcomes section.
- •The graduate will develop advanced skills in data management, including working with both relational and non- relational databases. They will be proficient in designing, implementing, and managing cloud-native data architectures, ensuring scalability, security, and efficiency in handling large-scale data systems.
- •The graduate will gain competencies in automating data flows within analytics systems using Extract, Transform, and Load (ETL) processes. They will be adept at designing and implementing data pipelines, both batch and streaming, to process and transform data efficiently within cloud environments, supporting real-time analytics and large-scale data processing.
- •The graduate will be skilled in using programming languages such as Python and R to perform data acquisition, organization, and analysis. They will also be proficient in applying statistical data mining techniques, including supervised and unsupervised machine learning, to derive insights from complex datasets and inform business decisions.
Areas of Study
2 groups · 11 coursesCourse groups from the WGU Program Guide. Expand each group to see course descriptions and competencies.
Course Roster (11 courses)
WGU Catalog 2026-03Term 2
Total: 32 CUs across 11 courses. Degree total per catalog: 32 CUs.