DSE 203Data Integration and ETL
The course is designed to provide students with the fundamentals of data integration and includes schema mapping and matching, entity disambiguation, ontology development and management, data provenance, and crowd sourcing and machine learning as strategies for integration. The course will also require hands-on projects in which students will work on a data integration problem requiring integration of two or more datasets taken from an application domain of their choice (e.g., geospatial data, healthcare, financial applications, bioinformatics, etc.).
Prerequisites
None listed in the catalog.