Objectives and outcomes
Students are acquainted with the modern principles of information management, data and the design of modern information systems, based on an object-oriented approach and relational databases. Students acquire advanced knowledge and skills related to data and information management, design and development of information systems.
Lectures
Basic concepts of data science. Historical overview of the development of data storage methods, data management and reporting. Data modelling, knowledge and information: set, binary relation (key-value, hashing and index), n-ary relation (table), tree (XML) and graph. Abstractions and reduction of n-ary relation to binary, sorting of binary relation, indices, tree traversal and graph search. Codd’s relational model. Relational algebra as an engine for generating reports, SQL. Information system design. Requirements analysis. Logical design of the structure and dynamics of the information system, SSA. Object-oriented approach to information systems modelling – UML. Requirements analysis in an object-oriented approach. Use cases. Description of the dynamics of the information system. Sequence diagrams. Conceptual model of the system. Patterns in IS modelling. Implementation in a real environment. Designing a relational database based on the UML object model. Object relational brokers, Hibernate. Database management systems, Oracle, MSSQL, PostgreSQL Object databases, MongoDB.
Practical classes
Analysis of the system and user requirements. An example of database design: normalization of relations. IS analysis and design. Functional decomposition, SSA. Data dictionary. PMOV. IDEF1X, IE. Examples of object-oriented design using UML notation. Use cases. Multitier application architecture. Sequence diagrams. Using a key-value Redis database to cache data. Application of Hibernate broker.