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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
DAT335 - Data Management
Systematisk datahantering
Syllabus adopted 2017-02-23 by Head of Programme (or corresponding)
Owner: TKITE
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: First-cycle
Major subject: Computer Science and Engineering, Information Technology

Teaching language: English
Application code: 52133
Open for exchange students: No
Block schedule: B+
Maximum participants: 15
Only students with the course round in the programme plan

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0117 Examination 4,5 c Grading: TH   4,5 c   16 Mar 2020 am L,  09 Jun 2020 am L,  19 Aug 2020 pm L
0217 Written and oral assignments 3,0 c Grading: UG   3,0 c    

In programs



Philipp Leitner

  Go to Course Homepage


In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.


The course introduces the students to the role of data, information, and knowledge in
software engineering. The course has two general themes: (1) fundamental concepts
related to data in software engineering; (2) basic principles of database systems as seen
by users, application programmers and database administrators.

Learning outcomes (after completion of the course the student should be able to)

Knowledge and understanding
  • explain the differences between data, information and knowledge,
  • explain the concepts related to software metrology and information visualization,such as measure, measuring system, dashboard and indicator,
  • explain basic concepts: relational data model, non-relational data model, entityrelationship model, relational database design, relational algebra and the databaselanguage SQL,

Skills and abilities
  • construct an algorithm for filtering and visualizing data based on a predefinedcriteria,
  • manage the process of collecting and representing data in a database,
  • build a data model (entity-relationship model),
  • create database tables, and formulate database queries in SQL,
  • experiment with data technologies such as big data and open data,
Judgement and approach
  • assess the quality of data and correctness of data models,
  • evaluate the applicability of data management techniques for a given purpose.


The course introduces concepts and techniques related to working with data,
information and knowledge, although the focus is mostly on data and information.
Techniques related to extraction, representation, modeling, access, and visualization of
data are discussed. The course then introduces the role of databases and database
management systems, covering topics such as algebra and the relational database,
logical and physical design of databases, and the use of SQL. This includes
programming in SQL, from the perspective of a user querying or modifying an existing
database, by a database designer, and by an application programmer invoking SQL
from a host language. The course also highlights the difference between SQL and
NoSQL and covers different data models such as XML, RDF, and JSON.


The teaching consists of lectures, group work, exercises, as well as supervision in
connection to the exercises.


Course literature to be announced the latest 8 weeks prior to the start of the course.

Examination including compulsory elements

Written exam and assignments.

Page manager Published: Thu 04 Feb 2021.