ECTS credits: 5
Lectures: 2
Exercises: 2

Course objective:

To teach students how to use methods and information technology as support to decision-making.

Course contents:

Introduction to decision-making and DSS (Data Decision Systems). DSS architecture. ERP systems. Business intelligence. Expert systems. Data warehousing. Meta data and their management. Dimension database. OLAP. Mining. Neuron networks methodology. Systems for reporting and presentations.

Competences:

Students shall learn methods for conceptual, logical and principles of physical modeling. They shall gain elementary knowledge on information systems for support to decision-making, their architecture, use, implementation and maintenance. With the completion of the class, they shall be able to take part in teams for planning and DSS system implementation.

Learning outcomes:

Having passed the exam, the student will be able to: 1. Design a model for the preparation and storage of data. 2. Design and build an OLAP system. 3. Create business reports based on the data in the data storage. 4. Combine several systems into a single common one that will serve as support in decision-making 5. Estimate in which parts of operation of the information system it is suitable to use expert systems. These outcomes contribute to the learning outcomes of the study program: - Propose solutions to engineering problems in the profession (4). - Use the functionalities of contemporary engineering tools (5). - Present one's own or team work (11). - Use professional literature and search accessible information bases and knowledge bases (12).