Course Description
Modern computing applications require storage, management, and processing of petabytes of data. The data is not only extremely diverse, ranging from unstructured text and relational tables to complex graphs, but it is also dynamic. This course focuses on developing scalable architectures, algorithms, and techniques for supporting various data intensive applications.
Athena Title
ADV DATA INTSV COMP
Prerequisite
CSCI 4370/6370 or permission of department
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Course Objectives
1. The students will develop a deep understanding of the issues involved in storing and querying large amounts of various kinds of structured, unstructured and dynamic data. 2. The students will gain expertise in applying modern distributed computing paradigms, such as Map-Reduce, for processing and analyzing different kinds of data. 3. The students will obtain hands-on experience in developing data intensive systems and applications by working with frameworks such as Hadoop, Pig, Pegasus, and HBase.
Topical Outline
1. Introduction to data intensive computing 2. Internet-scale text data processing and information retrieval 3. Indexing, storing and querying large graphs 4. Spatio-temporal data management and location-aware services 5. Data stream processing and complex event processing 6. Distributed data storage systems 7. Cloud computing and the map-reduce framework 8. Scalable key-value stores
Syllabus
Public CV