13M111SIBP - Software Engineering of Large Databases

Course specification
Course title		Software Engineering of Large Databases
Acronym		13M111SIBP
Study programme		Electrical Engineering and Computing
Module
Type of study		master academic studies
Lecturer (for classes)		professor PhD Miloš Cvetanović
Lecturer/Associate (for practice)		asst. MA Tamara Šekularac Obradović, electrical and computer engineer
Lecturer/Associate (for OTC)		asst. MA Tamara Šekularac Obradović, electrical and computer engineer
ESPB		6.0	Status	elective
Condition		Data base management systems
The goal		Understanding the architectures of modern DBMS for large scale structured and non structured databases, different possibilities for their analytical processing and integration and evaluation the different commercial tools.
The outcome		Students will be able to use modern DB technologies, NoSQL, NotOnlySQL, LogicalDataWarehouse, InMemoryComputing, and BigData, which are the basis for development of IoT, Cloud, SmartMachines and BYOD, and: •Evaluate the different DBMS and their features •Complete implementation of selected case study from the Experience Repository; •Gain practical experiences on using industry-strength tools.
Contents
Contents of lectures		DB Taxonomy: DBMS models and architectures:NoSQL, NotOnlySQL, LogicalDataWarehouse, InMemoryComputing, BigData; DB integration: language-oriented (embedded SQL); driver-oriented (ODBC, JDBC) (architectures, driver types, application scenarios); component-based; SOA integration; Web Services; agent-based; IoT, Cloud, SmartMachines, BYOD. AMDD development methodology.
Contents of exercises		Identification of design challenges using AMDD development methodology. Evaluation of the different commercial tools: NoSQL (mongoDB, Cassandra, Hypertable,CouchDB) i BigData (Hadoop, ApacheSpark). Students, organized in teams, select an appropriate project proposal from the Experience Repository (ER), design, implement and document the development process.
Literature
Modern Database Management (10th Edition) by Jeffrey A. Hoffer, V. Ramesh, and Heikki Topi (Hardcover - Jul 29, 2010) (Original title) Tiwari S, „Professional NoSQL“, John Wiley & Sons, Inc., SAD, 2011 (Original title) Sangeetha, S., & Sreeja, A. K. (2015). No Science No Humans, No New Technologies No changes" Big Data a Great Revolution. (Original title) NoSQL Databases by Christof Strauch https://www.christof-strauch.de/nosqldbs.pdf (Original title) Bernard Marr, Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things Paperback – 2017 (Original title)
Number of hours per week during the semester/trimester/year
Lectures	Exercises	OTC	Study and Research	Other classes
2	2	1
Methods of teaching		Instructional methods include classical lectures, class discussions, individual homeworks (practical projects) and email discussion list.
Knowledge score (maximum points 100)
Pre obligations		Points	Final exam	Points
Activites during lectures		0	Test paper	30
Practical lessons		0	Oral examination	0
Projects		70
Colloquia		0
Seminars		0