Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: Big Data Systems (17.IZMI04)

Native organizations units: No data

Type of studies	Title
Master Academic Studies	Information Systems Engineering (Godina: 1, Winter)
Master Academic Studies	Mathematics in Engineering (Godina: 2, Winter)

General information:

Category	Professional-applicative
Scientific or art field	Information-Communication Systems
Interdisciplinary	No
ECTS	4

Educational goal:

The course provides students with the knowledge of methods and techniques used for storage, access, analysis and mining of Big Data.

Educational outcome:

Upon completing this course successfully, students will be able to efficiently use contemporary systems aimed at storage, access, analysis and mining of big structured and unstructured data collections. Students will be skilled to use and develop storage and processing systems of big data, based on several technologies like Hadoop and High Performance Computing Platform (HPCC).

Course content:

Storage, scalability and availability of big data. CAP theorem, ACID vs. BASE database features. Alternate database systems (NoSQL). NoSQL database systems: properties, advantages and challenges. Classification and comparison of NoSQL databases. Key-value databases. Column-oriented databases. Graph-oriented databases. Document databases. Temporal and spatial databases. Data mining basic concepts. MapReduce and HPCC approach to parallel and distributed processing. Data stream analysis, clustering techniques, discovering association rules, recommendation systems, social network graphs analysis, dimensionality reduction techniques, machine learning techniques for big data. The theoretical instruction will be accompanied by the practical training focused on the use of solutions in the domain of big data based on Hadoop and HPCC technologies.

Teaching methods:

Lectures; Study and research work; Consultations; Individual work on required assignments. Students are encouraged to communicate, to participate in critical discussions; to work independently and to be actively involved in teaching process.

Literature:

Authors	Title	Year	Publisher	Language
Sharda, R., Delen, D., Turban, E.	Business Intelligence, Analytics and Data Science - A Managed Perspective	2017	Pearson, New York	English
Eric Redmond, Jim R. Wilson	Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement	2012	The pragmatic Bookshelf	English
Sadalage J. P., Fowler M.	NoSQL Distilled A Brief Guide to the Emerging World of Polyglot Persistence	2013	Pearson Education, Inc.	Serbian language
Anand Rajaraman, Jure Leskovec, Jerey D. Ullman	Mining of Massive Datasets	2011	Cambridge University Press	English
Elmasri R, Navathe S. B,	Fundamentals of Database Systems, 7th Edition	2015	Pearson Education Limited	English
Ćulibrk, D.	Otkrivanje znanja iz podataka : odabrana poglavlja	2012	Create Space, Fortlauderdale	Serbian language
Shashank Tiwari	Profesisonal NoSQL	2011	John Wiley & Sons, Inc.	English