Study Guide

Objective

The student knows how to choose, design and apply a suitable data management system (SQL and/or NoSQL) for their software project. The student is able to use advanced data management techniques based on authentication, authorization and, for example, handling complex large datasets efficiently.

Content

- Design and implementation of the chosen data management system
- Implementing the authentication and authorization
- Managing large complex datasets (e.g. aggregation and indexing, etc.)
- Maintaining system performance and quality of data
- Data filtering
- Analytics

Location and time

Lectures will be kept in Lapland UAS, Rovaniemi. We will use computer rooms at Rantavitikka campus

Materials

Study material will be distributed in moodle.

Teaching methods

There will be about 40 hours lectures. During the lectures we study the course topics and also get knowledge how to compile the course works.

Also a semester project will be part of the course and evaluation criteria.

Content scheduling

Database design
NoSQL databases
Authentication and authorization
Big data, aggregations and indexes
Perfomance and data quality
Filtering data, python

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is able to implement SQL- and/or NoSQL-based data management applications acknowledging basic level of information security under guidance.

Assessment criteria, good (3)

The student is able to implement SQL- and/or NoSQL-based data management applications acknowledging basic level of information security independently. The student is also able to apply some advanced filtering techniques as well as monitor and manage the system performance in their data management system.

Assessment criteria, excellent (5)

The student is able to implement SQL- and/or NoSQL-based data management applications and apply advanced level of information security independently. The student is also able to proactively apply advanced filtering techniques as well as monitor and manage the system performance in their data management system based on their own consideration.