681 Data Management Technologies

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.

    2. Content

    Course topics:

    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)

    Tutorial topics:

    • 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.

    3. Readings

    • 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.

    Application:

    • Using acquired knowledge and tools for data management in engineering and research work.

    Reflection:

    • Introduction and comprehension of connections between specific theoretical data management technologies, and their practical use.

    Transferable skills:

    • 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).

    6. Assessment

    • Continuing (homework, midterm exams, project work) (60%)
    • Final: (written and oral exam) (40%)