03948ntm a22005897i 4500 000716588 CZ-PrVSE 20241005123452.0 m d cr n|||||||||| 241005s2024 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Steigauf, Richard ISIS:149161 dis Rámce pro zlepšení kvality dat v životním zajištění eng Frameworks for Data Quality Enhancement in Life Reinsurance / Richard Steigauf 2024 ?? stran : digital, PDF soubor Vedoucí práce: Miloš Maryška Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2024 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2024 The master's thesis introduces an improved framework to enhance data quality in the field of life reinsurance, where precise data is essential for effective decision-making and risk management. The thesis acknowledges the challenges posed by inconsistencies in client-submitted data and proposes a comprehensive solution that can be seamlessly integrated into existing data processing infrastructure. The primary goal is to enhance the quality of data in life reinsurance through the development and implementation of strategic improvements. This involves establishing an advanced data profiling process to understand the structure, content, relationships, and patterns within life reinsurance data, achieved through a data assessment phase to evaluate and ensure data quality. Additionally, the thesis outlines the design of data quality checks tailored to the specific business needs and challenges in the reinsurance domain. It also proposes mechanisms for effective data correction to accurately and efficiently address identified issues. The thesis emphasizes the development of an improved reporting system for data quality problems, providing transparent insights into existing data quality discrepancies and enabling stakeholders to take appropriate actions. Beyond practical applications, the thesis delves into a theoretical exploration of data quality and management principles, examining broader concepts and methods beyond the specific context of reinsurance. This theoretical foundation not only supports the proposed practical framework but also contributes to the broader academic discourse on data quality management, with significant implications for operational efficiency and decision-making accuracy across various industries. Způsob přístupu: Internet business intelligence [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas data quality checks life reinsurance Business Intelligence data profiling data assessment data quality framework data quality reporting data quality data management data correction Power BI reporting Maryška, Miloš ola2012698940 ths Espinoza, Felix ISIS:5337 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/86305/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/86305 Hlavní práce https://insis.vse.cz/zp/86305/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/86305/posudek/oponent/81796 Oponentura https://insis.vse.cz/zp/86305/podrobnosti dc:identifier NEPOSILAT VSKP vse86305 241001 86305