Syftet med denna studie var att utveckla en generell applikation som kan generera DDL-skript från tre olika databaser: Oracle, SQL Server och DB2, genom att enbart använda en JDBC-uppkoppling. Behovet av denna studie kommer från att databasadministratörer och utvecklare effektivt ska kunna hantera databaser med olika system med varierande syntax och struktur. Processen genomfördes i IDEAn IntelliJ med java.sql-APIt för databasoperationer. Resultatet visade att trots skillnaderna mellan dessa databaser var det möjligt att utveckla en generell process för att extrahera DDL-kod med endast en JDBCuppkoppling. Dock krävdes vissa specifika anpassningar för varje databassystem. En observation var hanteringen av primärnycklar och index mellan systemen. Denna applikation har potential att vidareutvecklas till ett kraftfullt verktyg för databashantering, vilket sparar tid och resurser. Områden för framtida undersökning inkluderar hantering av komplexa datatyper och strukturer, samt prestanda med stora databaser. / This study was aimed at developing a generic application capable of generating DDL-code from three different databases: Oracle, SQL Server and DB2 by using JDBC. This research necessity origins from database administrators and developers need to effectively manage databases across different systems with different syntax and structure. The process was conducted in the IDEA IntelliJ using the java.sql-API for database operations. The result showed that despite the differences between these databases it was possible to develop a generic process for extracting DDL-code only using a JDBC connection. However, some specific adaptions were required for each database system. An observation was the managing of primary keys and indexes across the systems. This application has the potential to be developed further into a powerful tool for database management that saves time and resources. Areas for further investigation is handling of complex data types and structures and performance with large databases.

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The diploma thesis deals with synthetic data, selected approaches to their generation together with a practical task of data generation. The goal of the thesis is to describe the selected approaches to data generation, capture their key advantages and disadvantages and compare the individual approaches to each other. The practical part of the thesis describes generation of synthetic data for teaching knowledge discovery using databases. The thesis includes a basic description of synthetic data and thoroughly explains the process of their generation. The approaches selected for further examination are random data generation, the statistical approach, data generation languages and the ReverseMiner tool. The thesis also describes the practical usage of synthetic data and the suitability of each approach for certain purposes. Within this thesis, educational data Hotel SD were created using the ReverseMiner tool. The data contain relations discoverable with SD (set-difference) GUHA-procedures.