Course syllabus adopted 2021-02-17 by Head of Programme (or corresponding).
Overview
- Swedish nameAvancerade databaser
- CodeDAT475
- Credits7.5 Credits
- OwnerMPDSC
- Education cycleSecond-cycle
- Main field of studyComputer Science and Engineering, Software Engineering
- DepartmentCOMPUTER SCIENCE AND ENGINEERING
- GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Course round 1
- Teaching language English
- Application code 87114
- Block schedule
- Open for exchange studentsYes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0121 Written and oral assignments 3 c Grading: UG | 0 c | 0 c | 0 c | 3 c | 0 c | 0 c | |
| 0221 Examination 4.5 c Grading: TH | 0 c | 0 c | 0 c | 4.5 c | 0 c | 0 c |
|
In programmes
- MPALG - COMPUTER SCIENCE - ALGORITHMS, LANGUAGES AND LOGIC, MSC PROGR, Year 1 (elective)
- MPCSN - COMPUTER SYSTEMS AND NETWORKS, MSC PROGR, Year 1 (elective)
- MPDSC - DATA SCIENCE AND AI, MSC PROGR, Year 1 (compulsory elective)
- MPHPC - HIGH-PERFORMANCE COMPUTER SYSTEMS, MSC PROGR, Year 1 (elective)
Examiner
Graham Kemp- Professor, Data Science and AI, Computer Science and Engineering
Eligibility
General entry requirements for Master's level (second cycle)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Specific entry requirements
English 6 (or by other approved means with the equivalent proficiency level)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Course specific prerequisites
To be eligible to the course, the student should have a Bachelor's degree in any subject, or have successfully completed 90 credits of studies in computer science, software engineering, or equivalent.Specifically, at least 15 credits of successfully completed courses in programming or equivalent are required. The student also needs to have attended a course in databases of at least 7.5 credits (e.g. TDA357 Databases or DAT335 Data management).
Aim
Database management systems have been around for over fifty years. While relational database systems have been the dominant database technology, other kinds of non-relational systems have been in and out of fashion throughout that time, and today many applications are better supported by a variety of non-relational systems that have emerged in recent years. These include NoSQL systems, including graph databases, and systems based on Semantic Web standards. This course provides an overview of todays database management system landscape and highlights major trends. The course also includes concepts related to the implementation of database management systems since it is necessary to understand these concepts in order to appreciate the advantages and disadvantages of different database management systems. The purpose of this course is to provide a deeper understanding of databases, building on knowledge from an earlier introductory database course.Learning outcomes (after completion of the course the student should be able to)
Knowledge and understanding- describe concepts relating to the implementation of database management systems
- compare and contrast features of relational and non-relational database management systems
Skills and abilities
- construct Web ontology language statements corresponding to an Entity-Relationship diagram
- construct RDF (Resource Description Framework) triples that contain data for a given domain
- implement a graph database for a given domain
- retrieve data using declarative query languages for graph databases
Judgement ability and approach
- discuss advantages and disadvantages of different database design decisions
- discuss advantages and disadvantages of alternative query plans
- discuss suitability of different database management systems for various tasks
Content
Course contents:
- database management system architecture and implementation
- concurrency and recovery
- indexes
- query processing and optimization
- Semantic Web; RDF; RDF Schema; SPARQL
- ontologies
- NoSQL systems; aggregation-orientation; CAP theorem
- querying graph databases
- database applications
Organisation
The course consists of weekly lectures and exercise sessions, as well as supervised lab sessions.Literature
Course literature to be announced the latest 8 weeks prior to the start of the course.Examination including compulsory elements
Written individual exam given in an examination hall and programming assignments. The programming assignments are normally carried out in pairs.The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.