Subject: Data Management (17.IMS322 )
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Specialised Academic Studies | Engineering Management (Year: 1, Semester: Summer) |
The goal of the course is to master basic knowledge and technologies for data management, which will enable students to develop competencies in the field of prediction of changes and patterns of behavior based on the system within the data warehouse. Students will be presented data models, data management technologies, data storage and engineering of structured and unstructured data stored within the organization or through cloud computing.
The student will acquire knowledge necessary to analyze and use both structured and unstructured data using technological solutions, tools and methodologies while understanding the data management model. Academic Specialist in Engineering Management for Digital Transformation will develop competencies for engineering and business planning based on data and methodologies for data management.
Data world. Structures and databases. Methods of data analysis. The science of data management in practice. Visualization of data. Data analysis. Machine learning. Visualization of data in business. Research design in the science of data management. Experimental models of data analysis and modeling. Data storage and processing. Data security. Prediction and projections in data management. Using predictive analysis in solving real business problems. The future of data management.
Teaching methods include lectures, lectures with examples, lectures of visiting lecturers and experts, simulation and modeling of communication strategies for a sustainable business. Exercises are created to encourage individuality, originality and innovativeness of students through mastering teamwork methods in data management projects, presenting and analyzing case studies, creating scenarios.. Exercises are partially implemented with a computer.
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| 2019 | English |
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Test | Yes | Yes | 20.00 |
| Oral part of the exam | No | Yes | 70.00 |
| Lecture attendance | Yes | Yes | 5.00 |
| Project | Yes | No | 20.00 |
| Exercise attendance | Yes | Yes | 5.00 |
Prof. Morača Slobodan
Full Professor
Lectures
Assistant - Master Savković Milena
Assistant - Master
Practical classes
Faculty of Technical Sciences
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© 2024. Faculty of Technical Sciences.