Syllabus for |
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| DAT335 - Data Management |
| Systematisk datahantering |
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| Syllabus adopted 2017-02-23 by Head of Programme (or corresponding) |
| Owner: TKITE |
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7,5 Credits
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| Grading: TH - Five, Four, Three, Fail |
| Education cycle: First-cycle |
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Major subject: Computer Science and Engineering, Information Technology
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Department: 37 - COMPUTER SCIENCE AND ENGINEERING
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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 |
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Credit distribution |
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Examination dates |
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Sp1 |
Sp2 |
Sp3 |
Sp4 |
Summer course |
No Sp |
| 0117 |
Examination |
4,5 c |
Grading: TH |
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4,5 c
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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 |
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3,0 c
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In programs
TKITE SOFTWARE ENGINEERING, Year 3 (elective)
TKITE SOFTWARE ENGINEERING, Year 2 (elective)
Examiner:
Philipp Leitner
Go to Course Homepage
Eligibility:
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.
Aim
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.
Content
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.
Organisation
The teaching consists of lectures, group work, exercises, as well as supervision in
connection to the exercises.
Literature
Course literature to be announced the latest 8 weeks prior to the start of the course.
Examination including compulsory elements
Written exam and assignments.