Study Guide

Objectives (course unit)

The student learns basic concepts, ideas and principles concerning database systems including big data systems. The student is able to install, configure and run a database system and to design and implement data content to it and handle it with SQL language. General big data system concepts are handled; the aim is that the student can install, configure and run a big data system and handle it’s data. Some of the most popular big data technologies are learned.

Content (course unit)

Course content is:
- General ideas of a database system,
- Data modelling and design techniques,
- Relational model, data handling with SQL language,
- Database programming,
- NoSQL databases
- General ideas of a big data system
- CRISP DM

Assessment criteria, satisfactory (1-2) (course unit)

Student knows database system concepts and ideas and recognises them in real running systems. The student is able to do modest maintenance works for existing database systems and participate partly in the design of new database systems.

Assessment criteria, good (3-4) (course unit)

Student understands database system concepts and ideas and can justify their existence in real running systems. The student is able to maintain existing database system structures and design of new database system parts.

Assessment criteria, excellent (5) (course unit)

Student knows and understands in depth database system concepts and ideas and is familiar with their existence in real running systems. The student is able to create new database system structures and make new designs in all areas of the database systems.

Exam schedules

No exam.

Assessment methods and criteria

Assignments and group work.

Assessment scale

0-5

Teaching methods

F2f teaching.
Assignments (the primary learning method).
Group work and presentation.

Learning materials

Moodle course with links to additional material.

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

Less than 30% of the exercises completed.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design small databases.
At least 30% of the exercises completed, and minimal group work completed/presented.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student knows the elements of good database design (e.g. normalization and indexing) and can implement small database applications.
At least 60% of the exercises completed, and good group work completed/presented.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student is understands the elements of good database design (e.g. normalization and indexing) and can implement small database applications. The student is able to critically evaluate basic applications and database design choices.
At least 90% of the exercises completed, and excellent group work completed/presented.

Objectives (course unit)

The student learns basic concepts, ideas and principles concerning database systems including big data systems. The student is able to install, configure and run a database system and to design and implement data content to it and handle it with SQL language. General big data system concepts are handled; the aim is that the student can install, configure and run a big data system and handle it’s data. Some of the most popular big data technologies are learned.

Content (course unit)

Course content is:
- General ideas of a database system,
- Data modelling and design techniques,
- Relational model, data handling with SQL language,
- Database programming,
- NoSQL databases
- General ideas of a big data system
- CRISP DM

Assessment criteria, satisfactory (1-2) (course unit)

Student knows database system concepts and ideas and recognises them in real running systems. The student is able to do modest maintenance works for existing database systems and participate partly in the design of new database systems.

Assessment criteria, good (3-4) (course unit)

Student understands database system concepts and ideas and can justify their existence in real running systems. The student is able to maintain existing database system structures and design of new database system parts.

Assessment criteria, excellent (5) (course unit)

Student knows and understands in depth database system concepts and ideas and is familiar with their existence in real running systems. The student is able to create new database system structures and make new designs in all areas of the database systems.

Exam schedules

No exam.

Assessment methods and criteria

Assignments and group work.

Assessment scale

0-5

Teaching methods

F2f and remote teaching. In practice, students may participate in a classroom of remotely via MS Teams.
Assignments (the primary learning method)
Group work and presentation

Learning materials

Moodle course with links to additional material.

Student workload

See the period timetable.

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

Less than 30% of the exercises completed.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design small databases.
At least 30% of the exercises completed, and minimal group work completed/presented.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student knows the elements of good database design (e.g. normalization and indexing) and can implement small database applications.
At least 60% of the exercises completed, and good group work completed/presented.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student is understands the elements of good database design (e.g. normalization and indexing) and can implement small database applications. The student is able to critically evaluate basic applications and database design choices.
At least 90% of the exercises completed, and excellent group work completed/presented.

Objectives (course unit)

The student learns basic concepts, ideas and principles concerning database systems including big data systems. The student is able to install, configure and run a database system and to design and implement data content to it and handle it with SQL language. General big data system concepts are handled; the aim is that the student can install, configure and run a big data system and handle it’s data. Some of the most popular big data technologies are learned.

Content (course unit)

Course content is:
- General ideas of a database system,
- Data modelling and design techniques,
- Relational model, data handling with SQL language,
- Database programming,
- NoSQL databases
- General ideas of a big data system
- CRISP DM

Assessment criteria, satisfactory (1-2) (course unit)

Student knows database system concepts and ideas and recognises them in real running systems. The student is able to do modest maintenance works for existing database systems and participate partly in the design of new database systems.

Assessment criteria, good (3-4) (course unit)

Student understands database system concepts and ideas and can justify their existence in real running systems. The student is able to maintain existing database system structures and design of new database system parts.

Assessment criteria, excellent (5) (course unit)

Student knows and understands in depth database system concepts and ideas and is familiar with their existence in real running systems. The student is able to create new database system structures and make new designs in all areas of the database systems.

Exam schedules

No exam.

Assessment methods and criteria

Assignments and group work.

Assessment scale

0-5

Teaching methods

Remote teaching. In practice, students may only participate remotely via MS Teams.
Assignments (the primary learning method)
Group work and presentation

Learning materials

Moodle course with links to additional material.

Student workload

See the period timetable.

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

Less than 30% of the exercises completed.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design small databases.
At least 30% of the exercises completed, and minimal group work completed/presented.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student knows the elements of good database design (e.g. normalization and indexing) and can implement small database applications.
At least 60% of the exercises completed, and good group work completed/presented.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

The student is familiar with data systems basics and can design and analyze small databases. The student is understands the elements of good database design (e.g. normalization and indexing) and can implement small database applications. The student is able to critically evaluate basic applications and database design choices.
At least 90% of the exercises completed, and excellent group work completed/presented.