Introduction to Database Systems, MSc SD (Spring 2024)

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 students have taken an introductory programming course (otherwise basic programming skills in Python are expected) and a discrete maths course such as Discrete Mathematics for SD (or have knowledge of basic discrete maths: 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. Mandatory homework assignments emphasise key aspects of the course.

Mandatory activities

The course has 4 mandatory assignments that receive general and/or individual feedback. To be eligible for the final examination, a minimum of three assignments must be submitted and approved. Requirements for approval are minimal and approval will be communicated via LearnIT. Deadlines will be advertised during the course on LearnIT. In the event that a student fails to have the mandatory activities approved and proceeds to take the ordinary exam, they will receive a grade of 'NA' (Not Approved) for their exam attempt. 

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:
A: Written exam on premises, External (7-point scale)
Exam variation:
A22: Written exam on premises with restrictions.

reexam

Exam type:
A: Written exam on premises, External (7-point scale)
Exam variation:
A22: Written exam on premises with restrictions.

Time and date

Ordinary Exam - on premises Fri, 17 May 2024, 09:00 - 13:00
Reexam - on premises Tue, 13 Aug 2024, 09:00 - 13:00