Big Data Management Systems and Tools

The University of Waterloo’s Big Data Management Systems and Tools course offers a comprehensive and hands-on exploration of the technologies and techniques used to manage and analyze massive volumes of structured and unstructured data. Designed for professionals and learners aiming to enter or advance in the data field, this course covers the full spectrum of big data systems—from traditional relational databases to modern NoSQL solutions and distributed architectures. Participants gain practical experience with industry-leading tools such as Hadoop, Spark, Cassandra, and MongoDB, while developing critical skills in data scalability, reliability, and real-time processing.

Through eleven in-depth modules, learners explore core concepts including reactive system design, data warehousing, distributed storage, stream processing, cloud analytics, and MLOps. The course blends foundational theory with applied learning, offering hands-on activities in Spark, HDFS, and cloud platforms like AWS and Azure. By the end, students are equipped to design, implement, and manage scalable big data infrastructures and analytical systems, making them valuable contributors to data-driven decision-making in both enterprise and research environments.

Admission Requirements

• Foundations of Data Science course OR a passing grade on the prior learning assessment.
• Working knowledge of Python.
• Degree in Engineering, Mathematics, or Computer Science is recommended, but not required.
• Basic knowledge of programming and programming languages is strongly recommended.

What You’ll Learn

• Understand the architecture of reliable big data systems.
• Describe how they differ from traditional systems.
• Use several NoSQL database management systems.
• Address the many challenges of working with data at scale.
• Use tools such as MongoDB and Spark to process large datasets.