Official course description:
Full info last published 13/05-20

Introduction to Database Design, MSc SD

Course info
Language:
English
ECTS points:
7.5
Course code:
KSINDAD1KU
Participants max:
125
Offered to guest students:
yes
Offered to exchange students:
-
Offered as a single subject:
yes
Price (single subject):
10625 DKK (incl. vat)
Programme
Level:
MSc. Master
Programme:
MSc in Software Design
Staff
Course manager
Associate Professor
Teaching Assistant
Teaching Assistant (TA)
Teaching Assistant
Teaching Assistant (TA)
Teaching Assistant
Assistant Lecturer
Teaching Assistant
Teaching Assistant (TA)
Teaching Assistant
Assistant Lecturer
Course semester
Semester
Forår 2020
Start
27 January 2020
End
31 August 2020
Exam
Exam type
ordinær
Internal/External
ekstern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract

The course covers fundamental techniques for developing data management and data analytics applications.

Description
The course covers fundamental techniques for developing data management and data analytics applications. The main part of the course deals with traditional relational database processing, including the theory and practice of modelling and querying a database. In the latter part of the course, the focus is on new developments for both traditional database applications and for modern data analytics applications.
Formal prerequisites
This course assumes basic ability to use a computer. We also assume that a student has taken an introductory programming course. (otherwise basic programming skills in Java are expected) and a discrete math course such as Discrete Mathematic for SD (or has knowledge of basic discrete math: logic, set theory and proofs).


Intended learning outcomes

After the course, the student should be able to:

  • Write SQL queries, involving multiple relations, compound conditions, grouping, aggregation, and subqueries.
  • Use relational DBMSs from a conventional programming language in a secure manner.
  • Suggest a database design in the E-R model and convert to a relational database schema in a suitable normal form.
  • Analyze/predict/improve query processing efficiency of the designed database using indices.
  • Reflect upon the evolution of the hardware and storage hierarchy and its impact on data management system design.
  • Discuss the pros and cons of different classes of data systems for modern analytics and data science applications.
Learning activities

Lectures cover the most important aspects of the curriculum, and also provide tools and methods for describing, creating and using databases. Weekly exercise sessions consist of assignments designed to further understand and apply the topics discussed in lectures. The course has 4 optional assignments.

Mandatory activities
The course has no mandatory assignment.

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data -  Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens Cambridge University Press; 1 edition (August 30, 2018)

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 45%
  • Lectures: 12%
  • Exercises: 14%
  • Assignments: 19%
  • Exam with preparation: 10%
Ordinary exam
Exam type:
C: Submission of written work, External (7-point scale)
Exam variation:
C22: Submission of written work – Take home
Exam submisson description:
The exam is 4 hours followed by random fraud control.

Aids allowed for the exam: Written and printed books and notes. E-books on laptops, iPads, and other e-book readers are permitted.
Students must use their own computer with the PostgreSQL database system installed, as well as the Zoom software system.
Take home duration:
1 day


reexam
Exam type:

Exam variation: