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|DA 5020 - Collecting, Storing, and Retrieving Data|
Studies how to build large-scale information repositories of different types of information objects so that they can be selected, retrieved, and transformed for analytics and discovery, including statistical analysis. Analyzes how traditional approaches to data storage can be applied alongside modern approaches that use nonrelational data structures. Through case studies, readings on background theory, and hands-on experimentation, offers students an opportunity to learn how to select, plan, and implement storage, search, and retrieval components of large-scale structured and unstructured information repositories. Emphasizes how to assess and recommend efficient and effective large-scale information storage and retrieval components that provide data scientists with properly structured, accurate, and reliable access to information needed for investigation.
4.000 Credit hours
4.000 Lecture hours
Schedule Types: Seminar
Interdisc Studies - Provost Department
Graduate CCIS Data Sci Cert