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Curricular information is subject to change
After this module, students should be able to:
● Distinguish between structured and unstructured data, and explain common terminology from databases to data lakes
● Describe the ETL process
● Read, write and manage databases using SQL
● Distinguish different types of unstructured data, and their uses and typical methods of storing, accessing and processing them
● Define big data and the problems and some of the solutions associated with it
● Define real-time analytics and the problems and some of the solutions associated with it
● Describe the goals of data cleansing and curation and execute them in code
● Explain the issues of security, privacy and ethics in data, and bring these to bear on projects where appropriate
| Student Effort Type | Hours |
|---|---|
| Lectures | 24 |
| Computer Aided Lab | 24 |
| Autonomous Student Learning | 48 |
| Total | 96 |
Not applicable to this module.
| Description | % of Final Grade | Timing |
|---|---|---|
| Examination: Exam | 50 |
2 hour End of Trimester Exam |
| Project: Technical Project | 25 |
Throughout the Trimester |
| Continuous Assessment: Participation/Presentation | 25 |
Throughout the Trimester |
Compensation
This module is not passable by compensation
Resit Opportunities
No Resit
Remediation
If a resist is required students will be asked to undertake a project, to be decided at the time, which will encomapss the course curriculum.
| Name | Role |
|---|---|
| MSc Stefan Forstenlechner | Tutor |