Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: Data Management (17.IMS361)

Native organizations units: No data

Type of studies	Title
Specialised Academic Studies	Engineering Management (Godina: 1, Summer)

General information:

Category	Professional-applicative
Scientific or art field	Information-Communication Systems
Interdisciplinary	No
ECTS	5

Educational goal:

The course provides students with an overview of the key concepts for establishing a comprehensive data management strategy for an organization, ensuring that its operational and analytical needs are efficiently, effectively, and securely addressed. It reviews the data management challenges organization confront with and how data management and analytics is used to help make sound management decisions.

Educational outcome:

This course will examine the underlying principles and technologies needed to structure and capture data, validate and clean it, contextualize it, store it, access it, and use it safely and securely. Students will gain an understanding of: database systems and database design principles, relational database management systems and Structured Query Language; data analytics and visualization and how managers use analytics to formulate and solve business problems and to support managerial decision making.

Course content:

Key concepts of data, information, knowledge and database. Data life cycle. Fundamentals of data modeling. Conceptual, implementational and physical database design. Fundamentals of relational database management systems. Understanding and creating core database objects. Foundations of Structured Query Language: queries, views, constraints, and optimization. The data warehouse – basic concepts. An integration of data from different sources. Structured, semi-structured and unstructured data. Interpretation the business significance of the data and generating reports on the data, including appropriately constructed graphics and histograms that illustrate important features of the data. Data Quality. Data safety and security. Big data systems – opportunities and challenges.

Teaching methods:

Lectures; laboratory exercises; individual consultations; team work on the design of conceptual data base schema; individual work (assignments). Students are encouraged to communicate, to reason critically, to work independently and to contribute actively to teaching process.

Literature:

Authors	Title	Year	Publisher	Language
Elmasri R, Navathe S.	Fundamentals of Database Systems, 7/E	2015	Pearson Education Limited	English
Rick Sherman	Business Intelligence Guidebook - From Data Integration to Analytics, 1st edition	2014	Morgan Kaufmann	English
Mogin, P., Luković, I., Govedarica, M.	Principi projektovanja baza podataka	2004	Fakultet tehničkih nauka, Novi Sad	Serbian language
Mogin, P.	Strukture podataka i organizacija datoteka	1994	Student, Novi Sad	Serbian language
Christine L. Borgman	Big Data, Little Data, No Data: Scholarship in the Networked World	2015	Cambridge MA: MIT Press	English

Knowledge evaluation:

Course activity	Pre-examination	Obligations	Number of points
Complex exercises	Yes	Yes	30.00
Complex exercises	Yes	Yes	20.00
Oral part of the exam	No	Yes	10.00
Test	Yes	Yes	10.00
Test	Yes	Yes	10.00
Written part of the exam - tasks and theory	No	Yes	20.00