Introduction to Database Management, 7.5 Credits

Contents

This course covers the concepts and tools necessary to use database systems. This starts with introducing the relational and semi-structured models of data and then delving into the classic relational query languages (tuple calculus and relational algebra), normalization theory and entity-relationship modeling. This is followed by an in-depth coverage of SQL including its use in a server environment. The last part of the course covers semi-structured data models using XML and accessed via XPath/XQuery.

The course consists of two parts:
Part 1, principles, 4.5 credits:
This part covers the following topics: the relational model of data; the use of SQL, as both a stand-alone language and its use in applications with C, Java or Python as the host language, to express queries and updates as well as to declare schemata; the relational algebra and calculus; Entity Relationship-based schema design; and the normalization of relational schemata. The semi-structured data model as represented in XML and accessed in XPath/XQuery.

Part 2, practice, 3 credits. In the practice part some of the theories and techniques discussed in the principles part are put into practice. This consists of a series of mandatory practical assignments. 
 

Expected learning outcomes

Knowledge and understanding
After having completed the course the student will be able to:

• describe the relational model of data (FSR 1);
• explain what conceptual modeling is and how it is used in the development of database schemata (FSR 2);
• display sterling understanding of normal forms for relational schemata and describe algorithms to realize them (FSR 3);
• display a basic understanding of data modelling and querying in the context of semistructured data (FSR 4).

Skills and abilities
After having completed the course the student will be able to:

• display skill in declaring relational schemata using SQL (FSR 5);
• display broad competence in expressing queries and updates in SQL (FSR 6);
• develop interfaces to database-management systems using ODBC with one of C, Java or Python as the host language (FSR 7);
• express queries in the relational algebra and relational calculus (FSR 8);
• translate Entity Relationship specifications to relational schemata (FSR 9);
• design simple schemata in XML, represent data within those schemata, and express simple queries in XQuery/XPath on those schemata (FSR 10).

Required Knowledge

To be admitted to the course, 60 ECTS credits in Computing Science or two years of completed studies are required, in both cases including the courses (or equivalent):
1) Either CS2: Algorithms and problemsolving (5DV169) or Data Structures and Algorithms (5DV149/5DV150) and
2) CS4: Logic for computer science (5DV163) or 5DV102 Fundations of Logic and Model Theory or Mathematics courses comprising of 22.5 ECTS-credits.
3) Proficiency in English equivalent to Swedish upper Secondary course English A/5. Where the language of instruction is
Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.

Form of instruction

Instruction consists of lectures and mandatory assignments. In addition to scheduled activities, individual work with the material is also required.

Examination modes

The examination of Part 1 (FSR XX) consists of a six recitations worth 33 points each, and a written exam worth 800 points. The recitations are done by handing in a written solution to given problems and then participating in the recitations. Students are randomly chosen to present their solutions and the others students are expected do discuss and contribute to the solutions presented. The grades given are Fail (U), Pass (3), Pass with Merit (4), or Pass with Distinction (5). The grades are determined based on the following scale:

5: p >= 900
4: 900 > p >= 750
3: 750 > p >= 500
U: 500 > p

The examination of Part 2 consists of a three mandatory assignments that must be demonstrated to an adequate degree in a lab setting. The assignments are assessed as either complete or incomplete. In part 2, the grades given are Passed (G) or Fail (U). The part will be rated G/passed when all three mandatory assignments are assessed as completed. If a student participates in the examination but do not get all assignments assessed as completed at the end of the course, the grade U is given on the part.

On the course as a whole, the grades given are Fail (U), Pass (3), Pass with Merit (4), or Pass with Distinction (5). In order to pass the course, both mandatory parts must be passed. The final grade of the course is the grade of part 1

For all students who do not pass the regular examination there are additional opportunities to do the examination.

A student who has passed an examination may not be re-examined.

A student who has taken two tests for a course or a segment of a course, without passing, has the right to have another examiner appointed, unless there exist special reasons (Higher Education Ordnance Chapter 6, Section 22). Requests for new examiners are made to the head of the Department of Computing Science.

Examination based on this syllabus is guaranteed for two years after the first registration of the course. This applies even if the course is closed down and this syllabus ceased to be valid.

TRANSFER OF CREDITS
Students have the right to be tried on prior education or equivalent knowledge and skills acquired in the profession can be credited for the same education at Umeå University. Application for credit is submitted to the Student Services / Degree. For more information on credit transfer available at Umeå University's student web, www.student.umu.se, and the Higher Education Ordinance (Chapter 6). A refusal of crediting can be appealed (Higher Education chapter 12) to the University Appeals Board. This applies to the whole as part of the application for credit transfer is rejected.

Other regulations

This course may not be used towards a degree, in whole or in part, togehter with another course of similar content. If in doubt, consult the student counselors at the Department of Computing Science and / or the program director of your program.

In particular, this course can not, in whole or in part, be used in a degree together with 5DV119 Introduction to Database Management. The overlap between these two courses are 7.5 credits.

Course connections to programs and degrees
The course is a mandatory course for the Bachelor Of Science Programme in Computing Science, Master of Science Programme in Computing Science and Engineering, and can be included in the profile "Bioinformatics" in the Master of Science Programme in Biotechnology.