Data Storage and Management Technologies

The overall goal is for students to acquire in depth knowledge and skills so that they can manage data across a data tier in an efficient manner.

Knowledge and understanding
After completing the course, students will be able to:

• Explain how different data management platforms are used appropriately to handle different types of data.
• Explain how indexes can be used to optimise the retrieval of different types of data from a data tier.
• Explain how different types of cloud storage can be used to realise a data management platform.

Skills and abilities
After completing the course, students will be able to:

• Use programming languages to create stored APIs in a data tier.
• Use SQL to retrieve data from dimensional models.
• Create an information model for spatial data connected to an infrastructure network.

Evaluation ability and approach
After completing the course, students will be able to:

• Suggest a suitable data management platform for a specific situation with different types of data.
  

The course deals with how companies and organisations based on their different needs can choose a data management platform that is well suited for the type of data to be stored in their data tier. The course addresses various current data management systems and how they can be used effectively. It also discusses how indexes and design patterns can be used to optimise performance and response times for these data management platforms. The course deals with how to create information models for spatial data that is used to connect different types of phenomena to different infrastructure networks, where phenomena can be road surfaces, hospitals, speed cameras, etc.

Assignment (3 credits) and laboratory work (4.5 credits).

Lectures, laboratory work and assignments.

The Swedish grades U–VG.

Laboratory work U-G.
The final grade is determined by the assignment.