Topic 1

Lesson 1. Computer Technologies for Data Processing and Open Data

Objective: formation of students with a holistic system of knowledge, analytical thinking and practical competencies in the field of computer data processing technologies, Data Literacy culture and the use of open government data for effective decision-making. The student must master the phenomenon of data in the digital economy, the ontological concept of DIKW (Data - Information - Knowledge - Wisdom), the concept and structure of Data Literacy, as well as the key stages of data life cycle management (DLM: collection, cleaning/ETL, storage, analysis, visualization, archiving). During the training, special attention is paid to mastering data classification methods (by structuredness and scalar types), studying the engineering framework of data quality metrics (completeness, accuracy, uniqueness, relevance, consistency), as well as studying the regulatory framework of Ukraine in the field of open data (Law "On Access to Public Information", Resolutions of the Cabinet of Ministers No. 835, No. 867) and the infrastructure of the Unified State Web Portal data.gov.ua. Students should learn to analyze and process machine-readable formats (CSV, JSON, XML, XLSX), perform automated collection via CKAN API, clean and normalize datasets, and evaluate the functionality and algorithms of GovTech/B2B services (Opendatabot, YouControl, VKURSI, Clarity App). An important practical result is the formation of the ability to critically evaluate open data, adhere to ethical norms and requirements of the legislation on personal data protection (GDPR), and build effective analytical solutions and dashboards based on objective facts to optimize management and technological processes.