Official course description:

Full info last published 15/01-21
Course info
Language:
English
ECTS points:
7.5
Course code:
BSINDBS2KU
Participants max:
77
Offered to guest students:
no
Offered to exchange students:
Offered as a single subject:
no
Programme
Level:
Bachelor
Programme:
BSc in Data Science
Staff
Course manager
Associate Professor
Course semester
Semester
Efterår 2020
Start
24 August 2020
End
31 January 2021
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 and set theory).

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 SQL programming constructs 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 activities

The course has 4 mandatory assignments. 3 of the assignments need to be completed and approved before you can take the examination. Deadlines will be advertised during the course on LearnIT. Approval will be communicated via LearnIT and general feedback will be given during subsequent exercise sessions.

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 submission description:
4 hour online take home exam.

Aids allowed:
Written and printed books and notes
E-books and/or other electronic devices
- E-books on laptops, iPads, and other e-book readers are permitted.
- Any course material can be accessed online or on your machine.
- Your own notes can be accessed in any form.
Specific software and/or programmes
- Students must use their own computer with the PostgreSQL database system and their database client of choice installed.
- Use of (online or local) drawing programs for ER diagram creation is permitted.
- Use of online documentation for PostgreSQL (https://www.postgresql.org/docs/) and SQL (e.g., https://www.postgresqltutorial.com and https://www.w3schools.com/sql/) is permitted.

Communication with others is strictly forbidden. This includes posting anything to the internet to sites such as stackexhange. Searching for information on the internet (“googling”) is forbidden.

Random fraud control with Zoom will be conducted right after the submission.

Student Affairs and Programmes will randomly select 20 % of students who will have to show up in Zoom to check authorship of submitted solutions. The selection of students for fraud control will be published in LearnIT right after the exam together with a link to the Zoom meeting.

More information in LearnIT before the exam.

(Please disregard the 1 day duration noted below.)
Take home duration:
1 day

Time and date