Popis predmeta

Course Description

The life cycle of data from their creation through transmission, processing, storage and use, both in operating systems and in analytical systems. Database architectures. Basic information systems components. Principles of data modeling. Different conceptual data models. Concepts of the relational data model. Normal forms. The process of converting from a conceptual to a relational model. Data Warehouse Architecture. Designing a data warehouse. Dimensional data model and OLAP. Semi-structured data models. Object-oriented data models. Data Formatting for the Semantic Web. Ways to collect and transform data. Data cleaning procedures. Data clustering algorithms. Association rules method. NoSQL Database. Big Data Concepts. Possibilities of specific applications of data processing in the field of telecommunications.

Learning Outcomes

  1. Explain the data life cycle
  2. Design different types of data models with emphasis on the relational and dimensional models
  3. Design the information system architecture
  4. Understand data modelling for the Semantic Web
  5. Prepare data for analysis
  6. Apply basic data analysis methods
  7. Understand Big Data concepts and NoSQL databases

Forms of Teaching

Lectures

3 hours a week

Laboratory

data modeling, retrieving data etc.

Other

homework

Week by Week Schedule

  1. Evolution of database systems. Data models. Relational data model.
  2. Principles of data modeling, Conceptual modeling (ER model)
  3. Mapping an ER model to a relational schema
  4. Introduction to PL/SQL
  5. Semi-structured data model (expressed using XML, XML Schema, JSON). Data modeling for Semantic Web (RDF, OWL, SPARQL)
  6. Data warehouse architecture. Data warehouse design
  7. Dimensional model, On-Line Analytical Processing (OLAP). Building a data warehouse
  8. Midterm exam
  9. NoSQL databases, Big Data, data lake
  10. Cassandra - Big Data and distrubuted data processing
  11. Data preparation and exploratory data analysis
  12. Data preparation and exploratory data analysis
  13. Data mining
  14. Retrieving data from a relational database and query optimization
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Elective Courses of the Profile (1. semester) Elective Coursesof the Profile (3. semester)
Network Science (profile)
Elective Courses of the Profile (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) (3. semester)

Literature

Z. Skočir, I. Matasić, B. Vrdoljak (2007.), Organizacija obrade podataka, MERKUR A.B.D., Zagreb
Thomas Connolly, Carolyn Begg (2014.), Database Systems – A Practical Approach to Design, Implementation, and Management, Addison‐Wesley
Ralph Kimball, Margy Ross (2013.), The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, John Wiley & Sons
Marko Banek (2013.), Ontologije i Semantički Web (interna skripta),

For students

General

ID 223711
  Winter semester
5 ECTS
L3 English Level
L2 e-Learning
45 Lectures
15 Laboratory exercises

Grading System

Excellent
Very Good
Good
Acceptable

Learning Outcomes

  1. Explain the data life cycle
  2. Design different types of data models with emphasis on the relational and dimensional models
  3. Design the information system architecture
  4. Understand data modelling for the Semantic Web
  5. Prepare data for analysis
  6. Apply basic data analysis methods
  7. Understand Big Data concepts and NoSQL databases

Forms of Teaching

Lectures

3 hours a week

Laboratory

data modeling, retrieving data etc.

Other

homework

Week by Week Schedule

  1. Evolution of database systems. Data models. Relational data model.
  2. Principles of data modeling, Conceptual modeling (ER model)
  3. Mapping an ER model to a relational schema
  4. Introduction to PL/SQL
  5. Semi-structured data model (expressed using XML, XML Schema, JSON). Data modeling for Semantic Web (RDF, OWL, SPARQL)
  6. Data warehouse architecture. Data warehouse design
  7. Dimensional model, On-Line Analytical Processing (OLAP). Building a data warehouse
  8. Midterm exam
  9. NoSQL databases, Big Data, data lake
  10. Cassandra - Big Data and distrubuted data processing
  11. Data preparation and exploratory data analysis
  12. Data preparation and exploratory data analysis
  13. Data mining
  14. Retrieving data from a relational database and query optimization
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Free Elective Courses (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Elective Courses of the Profile (1. semester) Elective Coursesof the Profile (3. semester)
Network Science (profile)
Elective Courses of the Profile (3. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) (3. semester)

Literature

Z. Skočir, I. Matasić, B. Vrdoljak (2007.), Organizacija obrade podataka, MERKUR A.B.D., Zagreb
Thomas Connolly, Carolyn Begg (2014.), Database Systems – A Practical Approach to Design, Implementation, and Management, Addison‐Wesley
Ralph Kimball, Margy Ross (2013.), The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, John Wiley & Sons
Marko Banek (2013.), Ontologije i Semantički Web (interna skripta),

For students

General

ID 223711
  Winter semester
5 ECTS
L3 English Level
L2 e-Learning
45 Lectures
15 Laboratory exercises

Grading System

Excellent
Very Good
Good
Acceptable