BANL 4350 - Big Data Analytics

Prerequisites or Co-requisite: BANL 4300. The course examines the end-to-end lifecycle of big data, from its generation in transactional systems to its transformation into actionable insights. Students study the architecture and roles of big data databases supporting transactional, analytical, predictive, and generative AI applications, as well as efficient data structures, scalable storage platforms (e.g., Amazon S3), and distributed processing frameworks such as Hadoop and Apache Spark. Students investigate how vector databases support modern AI applications, particularly large language models, and how AI technologies reshape both operational cycle times and analytical workflows across industries. By the end of the course, students will be prepared to architect big data solutions that integrate storage, processing, and AI‑driven analytics-enabling organizations to unlock value from their data at scale and speed. 3 credits.