Data Systems and Analysis (5 op)

Osaamistavoitteet (Opintojakso)

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.

Sisältö (Opintojakso)

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

Arviointikriteerit, tyydyttävä (1-2) (Opintojakso)

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.

Arviointikriteerit, hyvä (3-4) (Opintojakso)

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.

Arviointikriteerit, kiitettävä (5) (Opintojakso)

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.

Tenttien ja uusintatenttien ajankohdat

No exam.

Arviointimenetelmät ja arvioinnin perusteet

Assignments and group work.

Arviointiasteikko

0-5

Opiskelumuodot ja opetusmenetelmät

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

Oppimateriaalit

Moodle course with links to additional material.

Arviointikriteerit - hylätty (0) (Ei käytössä, kts Opintojakson Arviointikriteerit ylempänä)

Less than 30% of the exercises completed.

Arviointikriteerit - tyydyttävä (1-2) (Ei käytössä, kts Opintojakson Arviointikriteerit ylempänä)

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.

Arviointikriteerit - hyvä (3-4) (Ei käytössä, kts Opintojakson Arviointikriteerit ylempänä)

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.

Arviointikriteerit - kiitettävä (5) (Ei käytössä, kts Opintojakson Arviointikriteerit ylempänä)

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.