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Data Systems and Analysis (5op)

Toteutuksen tunnus: 5G00DM01-3001

Toteutuksen perustiedot


Ilmoittautumisaika
03.06.2019 - 06.09.2019
Ilmoittautuminen toteutukselle on päättynyt.
Ajoitus
02.09.2019 - 20.12.2019
Toteutus on päättynyt.
Laajuus
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tietotekniikka
Toimipiste
TAMK Pääkampus
Opetuskielet
suomi
Koulutus
Bachelor's Degree Programme in Software Engineering
Opettajat
Erkki Hietalahti
Vastuuhenkilö
Pekka Pöyry
Opintojakso
5G00DM01

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.

Aika ja paikka

Fall 2019, weekday and time, place is in "lukkarikone". If there are changes I will inform with tabula messaging.

Tenttien ja uusintatenttien ajankohdat

-

Arviointimenetelmät ja arvioinnin perusteet

Bases on exercise / lab works activity. Grading:

Activity below 20 % => grade = 0
Activity between 20 % and 35 % => grade = 1
Activity between 35 % and 50 % => grade = 2
Activity between 50 % and 65 % => grade = 3
Activity between 65 % and 80 % => grade = 4
Activity above 80 % => grade = 5

Arviointiasteikko

0-5

Opiskelumuodot ja opetusmenetelmät

Theory lectures, exercises and lab works.

Oppimateriaalit

Elmasri & Navathe: Fundamentals of Database Systems. 7h edition. 2017 Pearson Global Edition.

Kroenke & Auer: Database Processing Fundamentals, Design, and Implementation. 14th edition. 2016 Pearson Global Edition.

Opiskelijan ajankäyttö ja kuormitus

Lecturing: 3 hours per week approximately 13 times.

You should reserve approximately 135 hours time to all works in this course (5 points times 27 hours per point).

Sisällön jaksotus

1. General database related topics
2. ER-modeling
3. SQL
4. Programming with databases
5. NoSQL databases
6. Big data systems

Toteutuksen valinnaiset suoritustavat

-

Harjoittelu- ja työelämäyhteistyö

-

Kansainvälisyys

-

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

Doesn't know the basic concepts handled in this course and cannot apply them.

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

A satisfactory understanding of the concepts and things taught in the course. Can apply them with help.

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

A good understanding of the concepts and things taught in the course. Can apply them independently.

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

An excellent understanding of the concepts and things taught in the course. Can apply them independently. Can discover new things in the area and learn them individually. Can apply the skills in new ways combining different areas of ICT systems.

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