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ICS 411 Big Data Storage and Processing

Covers the concepts and approaches that are used by big-data systems. Topics covered include: fundamentals of big data storage and processing using distributed file systems, the map-reduce programming paradigm, and NoSQL systems. Students will gain hands-on experience by implementing solutions to big data problems using tools like Hadoop, Apache Pig Latin, Hive, Impala, MongoDB, Cassandra, Neo4J, or Spark.

Prerequisites

Special information

First day attendance is mandatory.
Note: Students are responsible to both be aware of and abide by prerequisites for ICS courses for which they enroll, and will be administratively dropped from a course if they have not met prerequisites.
4 Undergraduate credits

Effective May 3, 2017 to present

Learning outcomes

General

  • Identify and justify the storage and processing requirements of data-intensive applications.
  • Explain the similarities and differences between the requirements of big-data applications and the ACID requirements of traditional database applications.
  • Analyze and solve data-intensive problems using Hadoop and the distributed file system.
  • Design and develop algorithms using the map-reduce programming paradigm.
  • Classify and describe NoSQL systems
  • Assess the suitability for using a particular type of NoSQL databases for an application