MØLBA3001 Data Engineering
- Course codeMØLBA3001
- Number of credits7,5
- Teaching semester2024 Autumn
- Language of instructionEnglish
- CampusLillehammer
- Required prerequisite knowledge
None
This course provides students with the knowledge, tools, and skills to capture, clean, transform, and load data for further use in the organization. The topics covered are:
- Data types, structures, and sources
- Data acquisition
- Storage and systematization of data in databases and data warehouses
- SQL
- Cloud solutions and programming interfaces
- Peculiarities of Big Data
- Role of data management in creating business value
Learning Outcome
Upon completion of the course, the candidate shall:
- Have advanced knowledge about data types and structures and their functionality (k1)
- Explain and exemplify the process of gathering data from various sources (k2)
- Have advanced knowledge of key concepts of data storage in databases and data warehouses (k3)
- Have advanced knowledge about relevant information technology such as cloud solutions, software as service (SaaS), and programming interfaces (k4)
- Have advanced knowledge of peculiarities of ”Big Data” with regards to gathering and storage (k5)
- Know about ethical and legal issues related to gather and store data (k6)
- Explain the role of data engineering in creating and maintaining business value (k7)
Upon completion of the course, the candidate shall be able to:
- Access and collect local and web-based data (f1)
- Extract, transform, and merge data using SQL (f2)
- Create and manipulate data sets of various data types using algorithms (f3)
- Contribute to designing or improving data storage and management systems in a business (f4)
Upon completion of the course, the candidate shall be able to:
- Plan the various stages of a data engineering project to make the data ready to consumers for analytics and decision-making (g1)
- Recommend computing tools and techniques for efficient implementation of such projects (g2)
The following teaching methods are used:
- Lectures
- Problem solving sessions
- Tutorial videos
- Case studies
- Quizzes
- Mandatory homework assignments must be handed in before each teaching module (a total of 4). Two will be individual, and two will be in groups. These will be combinations of practical and theoretical exercises covering key topics in the course.
- Three out of four homework assignments must be passed to be allowed to take the exam.
- Attendance on at least 50% of the courses lectured teaching.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Home exam | ECTS - A-F | Individual | 48 Hour(s) |
| 60 % | |
Written examination with invigilation | ECTS - A-F | Individual | 4 Hour(s) |
| 40 % |
- 48 hours take-home individual exam (counts 60% of the grade). The exam consists of practical assignments and a written report.
- Four-hour individual school exam under attendance (counts 40% of the grade).
Graded A-F, where E is minimum for passing the exam. Both exams must be passed for the student to pass the course.
Reading list
No reading list available for this course