Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Database systems
1.2 Code
BMEEOFTMI51
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lab | 2 |
1.5 Evaluation
Midterm grade
1.6 Credits
3
1.7 Coordinator
| name | Dr. Zoltán KOPPÁNYI |
| academic rank | Associate professor |
| koppanyi.zoltan@emk.bme.hu |
1.8 Department
Department of Photogrammetry and Geoinformatics
1.9 Website
1.10 Language of instruction
hungarian and english
1.11 Curriculum requirements
Compulsory in the Infrastructure Engineering (MSc) programme
1.12 Prerequisites
1.13 Effective date
2 February 2022
2. Objectives and learning outcomes
2.1 Objectives
The course aims to give the student an insight into the possibilities of analyzing large amounts of data. The efficient way of storing data and the basics of data organization will be presented during the semester. A further aim of the course is to get to know all the levels of developing a database system and develop project approach and teamwork skills.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
- familiar with relational databases,
- knows the steps of normalization and how to store data without redundancy,
- is familiar with the possibilities of modern databases,
- knows the SQL database management language.
B. Skills
- is able to create the specification of an engineering task that can be solved with databases,
- design a redundancy-free relational database based on a suitable specification,
- is able to implement a relational database in a database management system,
- is able to formulate analyzes using SQL language,
- able to automatically process and convert data sources and then load them into a database,
- capable of teamwork and communication.
C. Attitudes
- cooperates with the teacher and fellow students in expanding the knowledge,
- expands his knowledge with continuous acquisition of knowledge,
- open to the use of information technology tools,
- seeks to solve an engineering problem with the help of co-actors.
D. Autonomy and Responsibility
- able to keep in touch with colleagues on their own
- openly answers her colleagues ’questions and seeks professionally correct answers to them.
2.3 Methods
Lectures, exercises, written and oral communication, use of IT tools and techniques, independent and group work, work organization techniques.
2.4 Course outline
| Week | Topics of lectures and/or exercise classes |
| 1. | Introduction to the world of database analysis |
| 2. | History of databases, basic concepts, data models |
| 3. | Database design, redundancy, anomalies, and normalization |
| 4. | Case studies, legal and privacy concerns |
| 5. | Data types, graphical database analysis |
| 6. | Database design in practice, data conversion, and loading |
| 7. | Design patterns |
| 8. | SQL |
| 9. | SQL |
| 10. | SQL practice |
| 11. | Test |
| 12. | Reports and Forms |
| 13. | State of the art |
| 14. | Overview |
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
a) Books:
- Jeffrey D. Ullman - Jennifer Widom: Database systems - The Complete Book, 2008.
- Presentation slides
2.6 Other information
Teamwork: Students receive others’ assignments, add their work, and forward it to another student. Therefore, it is essential to understand the curriculum and follow the job description. If a question raises, students can contact all project members and solve raised issues together.
2.7 Consultation
Consultation dates: as specified on the website of the department, or by prior arrangement, by e-mail; e-mail: molnar.bence@epito.bme.hu
This Subject Datasheet is valid for:
2023/2024 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
Learning outcomes formulated in point 2.2 are assessed on one test, three homework assignments, and active participation in the exercises (partial performance assessment).
3.2 Assessment methods
| Evaluation form | Abbreviation | Assessed learning outcomes |
| 1st Test | T1 | A.1-A.4; B.4; C.3 |
| 1st Homework | HW1 | B.1 |
| 2nd homework | HW2 | A.1-A.2; B.2, B.4-B.6; C.1-C.4; D.1-D.2 |
| 3rd homework | HW3 | A.1, A.4; B.3-B.6; C.1-C.4; D.1-D.2 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Abbreviation | Score |
| T1 | 50% |
| HW1-HW2-HW3 | 50% |
| Sum | 100% |
3.4 Requirements and validity of signature
No signature can be obtained on the subject
3.5 Grading system
The grade of those who meet the conditions for attendance is determined according to the following criteria: At least 50% of the test must be completed. The final grade is calculated on the basis of the average of the test and the homework.
3.6 Retake and repeat
The first and second homework submitted and accepted can be corrected during the semester free of charge until the submission of the third assignment.
3.7 Estimated workload
| Activity | Hours/semester |
| participation in contact classes | 14×2=28 |
| preparation for the practices | 14×0.5=7 |
| preparing for performance evaluations | 5 |
| homework | 45 |
| independent acquisition of designated written curriculum | 5 |
| Sum | 90 |
3.8 Effective date
2 February 2022
This Subject Datasheet is valid for:
2023/2024 semester II