A user driven method for database reverse engineering

In this thesis we describe the UQoRE method which supports database reverse engineering by using a data mining technique. Generally, Reverse Engineering methods work by using information extracted from data dictionaries, database extensions, application programs and expert users. The main differences between all these methods rely on the assumptions made on the a-priori knowledge available about the database (schema and constraints on attributes) as well as the user competence. Most of them are based on the attribute name consistency. This paper presents a method based on user queries. Queries are stored in a “Query Base” and our system mines this new source of knowledge in order to discover hidden links and similarity between database elements

A Logical Design Methodology for Relational Databases Using the Extended ER Model

https://deepblue.lib.umich.edu/bitstream/2027.42/154152/1/39015099114723.pd

Generating a Normalized Database Using Class Normalization

Relational databases are the most popular databases used by enterprise applications to store persistent data to this day. It gives a lot of flexibility and efficiency. A process called database normalization helps make sure that the database is free from redundancies and update anomalies. In a Database-First approach to software development, the database is designed first, and then an Object-Relational Mapping (ORM) tool is used to generate the programming classes (data layer) to interact with the database. Finally, the business logic code is written to interact with the data layer to persist the business data to the database. However, in modern application development, a process called Code-First approach evolved where the domain classes and the business logic that interacts with the domain classes are written first. Then an Object Relational Mapping (ORM) tool is used to generate the database from the domain classes. In this approach, since database design is not a concern, software programmers may ignore the process of database normalization altogether. To help software programmers in this process, this thesis takes the theory behind the five database normal forms (1NF - 5NF) and proposes Five Class Normal Forms (1CNF - 5CNF) that software programmers may use to normalize their domain classes. This thesis demonstrates that when the Five Class Normal Forms are applied manually to a class by a programmer, the resulting database that is generated from the Code-First approach is also normalized according to the rules of relational theory

Performance optimization and security of EEG/ERP portal

Předmětem této práce je výkonová optimalizace a bezpečnost EEG/ERP portálu vyvíjeného na Katedře informatiky a výpočetní techniky. Portál slouží jako úložiště pro data a metadata získaná při výzkumných EEG měřeních. Teoretická část této práce ukazuje základní postupy pro optimalizaci databázového modelu, informace o objektově-relačním mapování spolu se způsobem použití nástroje Hibernate a zmiňuje časté problémy vyskytující se při navrhování datové vrstvy webových aplikací. V části zabývající se bezpečností jsou uvedeny nejrozšířenější bezpečnostní hrozby webových aplikací. Praktická část se zabývá především výkonovými problémy datové vrstvy EEG/ERP portálu. Dosažené výsledky jsou shrnuty a zhodnoceny a jsou navržena doporučení pro další zlepšení v oblasti datové vrstvy aplikace a v oblasti bezpečnosti.Katedra informatiky a výpočetní technikyObhájenoThe subject of this paper is divided into two parts: the performance and the security of the EEG/ERP Portal which serves as a repository for data and metadata from EEG research and which is developed at the Department of Computer Science and Engineering. The theoretical part of this thesis introduces common patterns of database model optimization, an overview of object-relational mapping together with the use of the Hibernate tool, and common issues in the database layer of the web applications. In the security part most common security threats are mentioned in overall. The practical part focuses mainly on the performance issues of the database layer of the EEG/ERP Portal. The results are then summarized and evaluated and recommendations for further improvements of the data layer and security level are given

Flexible view update

As uninstantiated windows onto a relational database, views are modified only when the intended update can be realized by updates against the underlying database. Such a conventional restriction can, and must, be relaxed when some relations, as collections of predicates, are composed of both basic and derived facts. Therefore, this paper presents an extended formulation for the problem of view updating based on two notions: the internal state and the perceptible state of a database. Through a clear distinction between these two database states, a mechanism is proposed to facilitate those legitimate view updates that are not necessarily translatable. The proposed mechanism also relies heavily on the normalization theory through functional dependencies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29857/1/0000205.pd

Master of Science

thesisData quality has become a significant issue in healthcare as large preexisting databases are integrated to provide greater depth for research and process improvement. Large scale data integration exposes and compounds data quality issues latent in source systems. Although the problems related to data quality in transactional databases have been identified and well-addressed, the application of data quality constraints to large scale data repositories has not and requires novel applications of traditional concepts and methodologies. Despite an abundance of data quality theory, tools and software, there is no consensual technique available to guide developers in the identification of data integrity issues and the application of data quality rules in warehouse-type applications. Data quality measures are frequently developed on an ad hoc basis or methods designed to assure data quality in transactional systems are loosely applied to analytic data stores. These measures are inadequate to address the complex data quality issues in large, integrated data repositories particularly in the healthcare domain with its heterogeneous source systems. This study derives a taxonomy of data quality rules from relational database theory. It describes the development and implementation of data quality rules in the Analytic Health Repository at Intermountain Healthcare and situates the data quality rules in the taxonomy. Further, it identifies areas in which more rigorous data quality iv should be explored. This comparison demonstrates the superiority of a structured approach to data quality rule identification

Methods to Build Optimal Database Model

The paper considers the search for optimal database models and effective ways of their building. Traditional data models are considered and their limitations and shortcomings are revealed during implementation in modern information systems. The main points of relational database normalization theory are studied as well as essential requirements to optimal database model are defined.У статті розглядається пошук оптимальних моделей баз даних та ефективних способів їх побудови. Розглядаються традиційні моделі даних, а також виявляються їх обмеження та недоліки при впровадженні в сучасні інформаційні системи. Вивчаються основні моменти теорії нормалізації реляційних баз даних, а також визначаються основні вимоги до оптимальної моделі бази даних.В статье рассматривается поиск оптимальных моделей баз данных и эффективных способов их построения. Рассматриваются традиционные модели данных, а также выявляются их ограничения и недостатки при внедрении в современные информационные системы. Изучаются основные моменты теории нормализации реляционных баз данных, а также определяются основные требования к оптимальной модели базы данных