Big Data Management & Analytics

Catalog description

Organizations today are generating massive amounts of data that are too large and unstructured to fit in relational databases. Existing platforms such as the Apache Hadoop allow for distributed and enterprise systems processing, of large data sets across clusters of computers, using the MapReduce programming model. In this course, students will gain an in-depth understanding of how MapReduce and Distributed File Systems work. In addition, they will be able to author Hadoop-based MapReduce applications in Java and use Hadoop subprojects Hive and Pig to build powerful data processing applications. Industry systems, such as IBM InfoSphere BigInsights and IBM InfoSphere Streams will be studied. Prerequisite Course(s): Prerequisite: CSCI 300 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3