University of South Florida 3 credits ISM
Introduces modern data engineering concepts and the design of data pipelines to support AI-enabled enterprises. Students examine extract-transform-load (ETL/ELT) methodologies, data warehouses, data lakes, streaming architectures, data fabrics, vector databases, and cloud-native data platforms, and learn how to design a high-level enterprise data architecture blueprint, and evaluate organizational and governance implications of pipeline design decisions. Emphasis is placed on architectural tradeoffs, platform selection, vendor evaluation, governance implications, cost-performance decisions, and organizational alignment rather than technical implementation. Technologies discussed include Snowflake, Databricks, major cloud platforms, and modern vector database systems. Prerequisite: None Corequisite: None USF Muma College of Business | School of Information Systems Credit Hours: 3
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