681 Data Management Technologies
- Study programme and level: University Study Programme in Administrative Information Science - 1st Cycle
- 3rd year
- 6 ECTS
- Course type: Core
- Lectures: 45
- Tutorial: 30
- Other forms of study: 15
- Individual work: 90
- Lecturer: Matjaž Kukar, PhD
1. Objectives and competences
- The main course objective is to present principles and approaches to data management from two points of view: external, focusing on proper database/data warehouse design and data preparation, and internal, focusing on intrinsic key database technologies.
External data management:
- Databases and data warehouses
- Database design:
- conceptual, logical and physical design
- advanced normalization,
- performance optimizaton
- Data warehouse design:
- design methodologies,
- data quality assurance,
- data analysis
- Non-relational database design (NoSQL)
- Non-relational data modeling
Internal data management:
- Assuring availability and consistency of stored data:
- concurrent data access,
- data archival and recovery
- distributed and parallel databases
- Query evaluation and optimization:
- query execution planning,
- estimating the costs of basic operations,
- alternative plan considerations
- Management of semi-structured and unstructured data types:
- modern non-relational database systems
- spatial and temporal data,
- other semi-structured data (audio, video, images, sequences, JSON, XML)
- Recognize typical data management problems and approaches for solving them
- Get to know various tools for database design and utilization, and use them in practical problems.
- Using the products of aforementioned tools for a practical database implementation (in terms of a substantial project)
Through the tutorial students get familiar with various data management tools and use them - in course of their projects – as a part of a practical problem solution. The final part of the project is a public presentation of the assigned problem, its solution and results.
- T. M. Connolly, C. E. Begg: Database Systems: A Practical Approach to Design, Implementation and Management, 4th edition, Addison Wesley, 2004.
- S. Sumathi, S. Esakkirajan: Fundamentals of Relational Database Management Systems, Springer, 2007.
- R. Ramakrishnan, J. Gehrke: Database Management Systems, 3rd edition, McGraw-Hill, 2002.
- Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement, Pragmatic Bookshelf, 2012
4. Intended learning outcomes
Knowledge and understanding:
- Recognizing data management problems, and understanding principles and approaches for solving them. Comprehension of basic concepts and usability of non-relational (NoSQL) databases.
- Using acquired knowledge and tools for data management in engineering and research work.
- Introduction and comprehension of connections between specific theoretical data management technologies, and their practical use.
- Database design, data storage, management and analysis are directly or indirectly being used in information systems, business intelligence, web services and intelligent systems.
5. Learning and teaching methods
- Lectures, homework and project work with explicit focus on simultaneous studies (for homeworks) and teamwork (for projects).
- Continuing (homework, midterm exams, project work) (60%)
- Final: (written and oral exam) (40%)