BIG DATA ANALYTICS (3 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Knowledge and understanding of core concepts, theories and principles of large-scale data storage and processing frameworks; Sound evaluation of opportunities and challenges related to leveraging those frameworks for building massive scale analytics solutions, and an ability to make recommendations to resolve these challenges; Proficient knowledge and use of at least one large-scale data store system, and at least one massive scale processing framework; Ability to design, develop, and evaluate an end-to-end analytics solution combining large-scale data storage and processing frameworks; Knowledge of cloud computing as a platform for Big Data analytics.

Topics:

1. Introduction to Big Data Analytics;
2. Big Data Analytics Platforms;
3. Big Data Storage and Processing;
4. Big Data Analytics Algorithms;
5. Linked Big Data: Graph Computing (Graph DB);
6. Linked Big Data: Graph Computing (Graph Analytics);
7. Linked Big Data: Graphical Models and Hardware Platform Issues;
8. Big Data Visualization