Popis predmeta

Course Description

Fullt-text search in relational databases, advanced use of SQL, object and object relational databases, geospatial databases, temporal databases, NoSQL databases, semantic web and data streams.

Learning Outcomes

  1. design object-relational, temporal, spatial and NoSQL databases
  2. use object-relational, temporal, spatial, stream and NoSQL databases
  3. explain the concepts of different data models

Forms of Teaching

Lectures

Students are presented with theoretical settings of selected topics intertwined with a multitude of practical examples.

Partial e-learning

Students have access to online tutorials designed to learn and master practical tasks.

Independent assignments

We encourage students to learn continuously by solving homework through a customized online platform and by creating several smaller projects in which they apply the knowledge acquired in the course.

Laboratory

Students discuss their own solutions to project tasks with subject teachers.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 40 % 10 % 40 % 10 %
Seminar/Project 50 % 50 % 50 % 40 %
2. Mid Term Exam: Written 0 % 20 % 0 %
Final Exam: Written 30 % 20 %
Exam: Written 50 % 25 %
Exam: Oral 25 %

Week by Week Schedule

  1. Principles of data modeling, Window functions, recursion, pivoting
  2. Window functions, recursion, pivoting, Project
  3. text search in relational database management system
  4. Object-oriented models, Object and object-relational databases
  5. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics
  6. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics, Project
  7. Distributed DBMS
  8. Midterm exam
  9. Key value, graph, column family, document, Semi-structured data model (expressed using XML, XML Schema, JSON), NoSQL databases
  10. Graph databases, Data replication and consistency models, The impact of indices on query performance, In-memory databases
  11. NoSQL databases, Graph databases, Big data concepts, Project
  12. Data modeling for Semantic Web (RDF, OWL)
  13. Data modeling for Semantic Web (RDF, OWL)
  14. Systems supporting structured and/or stream content, Stream databases
  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)
Elective Course of the Profile (1. semester) Elective Courses of the Profile (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)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Core-elective courses 1 (1. semester)

Literature

(.), Pramod J. Sadalage, Martin Fowler: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence,
(.), Tyler Akidau, Slava Chernyak, Reuven Lax: Streaming Systems,

For students

General

ID 222491
  Winter semester
5 ECTS
L2 English Level
L2 e-Learning
45 Lectures
15 Laboratory exercises

Grading System

87.5 Excellent
75 Very Good
62.5 Good
50 Acceptable

Learning Outcomes

  1. design object-relational, temporal, spatial and NoSQL databases
  2. use object-relational, temporal, spatial, stream and NoSQL databases
  3. explain the concepts of different data models

Forms of Teaching

Lectures

Students are presented with theoretical settings of selected topics intertwined with a multitude of practical examples.

Partial e-learning

Students have access to online tutorials designed to learn and master practical tasks.

Independent assignments

We encourage students to learn continuously by solving homework through a customized online platform and by creating several smaller projects in which they apply the knowledge acquired in the course.

Laboratory

Students discuss their own solutions to project tasks with subject teachers.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 40 % 10 % 40 % 10 %
Seminar/Project 50 % 50 % 50 % 40 %
2. Mid Term Exam: Written 0 % 20 % 0 %
Final Exam: Written 30 % 20 %
Exam: Written 50 % 25 %
Exam: Oral 25 %

Week by Week Schedule

  1. Principles of data modeling, Window functions, recursion, pivoting
  2. Window functions, recursion, pivoting, Project
  3. text search in relational database management system
  4. Object-oriented models, Object and object-relational databases
  5. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics
  6. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics, Project
  7. Distributed DBMS
  8. Midterm exam
  9. Key value, graph, column family, document, Semi-structured data model (expressed using XML, XML Schema, JSON), NoSQL databases
  10. Graph databases, Data replication and consistency models, The impact of indices on query performance, In-memory databases
  11. NoSQL databases, Graph databases, Big data concepts, Project
  12. Data modeling for Semantic Web (RDF, OWL)
  13. Data modeling for Semantic Web (RDF, OWL)
  14. Systems supporting structured and/or stream content, Stream databases
  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)
Elective Course of the Profile (1. semester) Elective Courses of the Profile (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)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Free Elective Courses (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Core-elective courses 1 (1. semester)

Literature

(.), Pramod J. Sadalage, Martin Fowler: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence,
(.), Tyler Akidau, Slava Chernyak, Reuven Lax: Streaming Systems,

For students

General

ID 222491
  Winter semester
5 ECTS
L2 English Level
L2 e-Learning
45 Lectures
15 Laboratory exercises

Grading System

87.5 Excellent
75 Very Good
62.5 Good
50 Acceptable