Subject: Business Intelligence and Data Warehouse Systems in Infrastructural Systems
(17 -
ESI087) Basic Information
Native organizations units
Course specification
Course is active from 30.07.2017.. Precondition courses
Advanced students' education in the data warehouse (DW) system development and its application in business intelligence, i.e. software support of strategic and tactic management in organization systems. Mastering data mining algorithms and techniques in the fields of information and decision support systems. Gaining necessary skills and knowledge for the design and implementation of business intelligence and data warehouse systems in industry and business domain. Utilization of DW systems within information and decision support systems. Characteristics, tasks and application domains of DW in power systems. Strategic system analysis as a prerequisite for the development of DW and business intelligence systems. Planning the DW system development process. A common methodology of the DW system development. A common DW system architecture. Enterprise DW systems and Data Mart systems. A common structure and the design of database schemas for DW systems. Methods and techniques of the initial load and subsequent refreshing of a DW database. Extraction, transforming and loading data into a DW database – ETL process. Computation of aggregated data in DW databases. Database Management Systems' mechanisms aimed at providing various DW system implementations. Preserving operational performances of DW systems. Decision support systems. OLAP tools and data analyses. Reporting techniques and tools. Data Mining techniques and tools in DW systems. The use in infrastructure system software model. Algorithms overview and data model in infrastructure systems. Numeric calculations in infrastructure systems. Teaching is performed through lessons, oral and computer exercises (in the computer classroom), as well as consultations. Through the teaching process, students are constantly motivated to an intensive discussion, problem oriented reasoning, independent study work and active participation in the whole lecturing process. The prerequisite to enter final exam is to complete all the pre-exam assignments by earning at least 30 points.
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