This course explores the foundational principles of modern data architecture and the evolution of data pipelines from traditional data warehousing models. Students will examine how structured and semi-structured data is ingested, modeled, transformed, and stored to support business intelligence and decision-making across organizations. The curriculum covers data modeling strategies, schema design, ELT workflows, cloud-native data platforms, and the integration of analytics tools within modern data ecosystems. Through hands-on projects, case studies, and applied exercises, participants will develop practical skills in designing scalable, efficient data pipelines and understanding their role in real-time business analytics.
This course is designed for undergraduate students pursuing business intelligence, analytics, or data-related roles, and emphasizes applied data engineering concepts, tool-based learning, and alignment with strategic decision-making needs introduced in earlier courses.
- Teacher: Parnell Dujour