Databases (5 cr)

Evaluation scale

H-5

Content scheduling

In this course, students learn to use and design relational databases as well as understand differences to NoSQL/document databases. First, students familiarize with database thinking and the principles of data management from a quality perspective. Key topics include data modeling using ER diagrams, relational schema representations and normalization technique for validating the quality of the database design. Second, students apply structured query language (SQL) to create a database (SQL DDL), and to manipulate and search data in the database (SQL DML). Last, students learn differences between SQL and NoSQL databases through designing and using MongoDB document database. The course consists of lectures, exercises, a practical work and final exam.


Topics cover at least:
- Relational DBMS and DB use
- Relational database design
- Basics of SQL
- Introduction to document database MongoDB

Objective

After completing the course the student can:
- understand different types of databases and evaluate their feasibility for different purposes.
- plan and implement a database based on requirements and search and modify data in the database
- use at least one well-known database management system
- can describe database management tasks

Content

- Different types of databases
- Definition, planning and implementation of databases
- SQL basics
- Database administration in DBMS

Materials

Lecture slides and examples by the teacher
Plenty of internet material available
Supporting books about relational databases and SQL are available on the Internet.
MongoDB has good tutorials and documentation as well.

Teaching methods

The course consists of
1) lecture and home exercises (small queries and design tasks)
2) personal practical work (creating your own database) and
3) exam (testing your acquired skills).

Lecture exercises are divided into weekly topics. Each week introduces a new topic that builds on top of previous weeks. Lectures tend to begin with an introduction to the topic, which includes practical examples and learning material. Exercises are done individually or in small groups and the teacher may help.

NOTE! Usually, the lecture exercises can be returned only by participating in the lecture session!

Exam schedules

A part of the approved grade is approved exam which will take place in the end of the course. The date will be announced during the course.

Pedagogic approaches and sustainable development

- Learning by doing and trial&error with lecture exercises,
- Introductory lectures and examples provided by the teacher.
- Collaborating with other students in the lectures.

Completion alternatives

Participation in the lecture is not compulsory, but exercises can be returned only during the lecture.

Student workload

Participating weekly in lectures (exercises): a' 3 hours * 13 = 40h
Home exercises 10h
Individual practical work 60h
Exam 3 hours + preparing 20h

Student workload is about 5-8 h / week if you are new to relational databases.

Evaluation methods and criteria

The course is graded from 0-5. The grade is based on collected points during the course.
The exam is compulsory part and must be passed with 40% of total points of the exam, in order to pass the course.

Division of points:
Lecture and home exercises 70 p points in total
Practical work 60 points
Exam 40 p points
Total 170 points

Course grading:
Points Grade
< 85 --> NOT PASSED
85 --> 1
102 --> 2
119 --> 3
136 --> 4
153 --> 5

Failed (0)

Less than 50% of total points collected or the exam is failed (less than 40% of total points of the exam). Check the points-to-grade table

Assessment criteria, satisfactory (1-2)

- Is able to implement relational database management software (DBMS) and know the tasks related to database maintenance
- Is able to design a relational database using conceptual model technique (ER or similar notation)
- Can implement a relational database with SQL statements
- Can retrieve, add and edit data in a relational database with simple SQL statements
- Knows different types of databases and their uses

Less than 70% of total points collected.

Assessment criteria, good (3-4)

In addition
- Can interpret the concept model and implement a relational database based on it
- Understands the meaning and use of keys and reference integrity in relational databases
- Is able to use SQL statements for data retrieval in various ways, such as combining data from different tables
- Understands the principle and purpose of normalization
- Can introduce non-relational databases and evaluate their suitability for different purposes (MongoDB)

70-90% of total points collected.

Assessment criteria, excellent (5)

In addition
- Is able to independently develop a high-quality concept model based on the user requirements
- Can use normalization to improve the quality of a relational database
- Can use SQL statements for information retrieval in various ways, such as sub-groupings and sub-queries
- Can do basic queries and design a simple NoSQL database (MongoDB)

More than 90% of total points collected.

Further information

All returns and communications take place through the Itslearning platform (except for the online course).

There are no pre-requisites for course performance in this course, and this course does not require previously acquired skills. It is necessary to have your own computer and know how to use it.
We use Python, the relational database and its management environment for practical training (MySQL, MariaDB, SQLite or similar used in UwAmp, XAMPP or WAMP or similar) and must be installed on the student's personal computer. The necessary applications are installed during a lecture together.
In addition to relational databases, students learn about MongoDB cloud services, Mongo Shell, and practice designing and using a document-based database.