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Detailed Course Information


Spring 2017 Semester
May 28, 2020
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DS 5110 - Introduction to Data Management and Processing
Introduces relational database management systems as well as modern parallel data processing systems such as MapReduce. Topics include relational algebra; SQL; stored procedures; user-defined functions; cursors; embedded SQL programs; client-server interfaces; entity-relationship diagrams; normalization; B-trees; concurrency; transactions; database security; constraints; object-relational DBMSs; and specialized engines such as spatial, text, XML conversion, and time series. Includes exercises using a commercial relational or object-relational database management system. Covers MapReduce programming, introduction to cloud computing, distributed databases, and distributed file systems.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
GSCS Computer & Info Science

Must be enrolled in one of the following Levels:     

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