194 research outputs found

    Elaboration d'entrepôts de données complexes

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    National audienceIn this paper, we study the data warehouse modelling used in decision support systems. We provide an object-oriented data warehouse model allowing data warehouse description as a central repository of relevant, complex and temporal data. Our model integrates three concepts such as warehouse object, environment and warehouse class. Each warehouse object is composed of one current state, several past states (modelling its detailed evolutions) and several archive states (modelling its evolutions within a summarised form). The environment concept defines temporal parts in the data warehouse schema with significant granularities (attribute, class, graph). Finally, we provide five functions aiming at defining the data warehouse structures and two functions allowing the warehouse class inheritance hierarchy organisation

    An overview of data warehouse design approaches and tecbniques

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    A Data Warehouse (DW) is a database that stores information oriented to satisfy decision-making requests. It ia a database with some particular features concerning the data it contains and its utilisation. The features of DWs cause the DW design process and strategies to be different frome the ones for OLTP Systems. This work presents a brief description of different approaches and techniques that address the DW design problem

    Uma proposta de especificação formal para data warehousing

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    Orientador: Martin A. MusicanteDissertação (mestrado) - Universidade Federal do Paran

    Uso de semântica de ações na especificação de um sistema de data warehousing

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    Data warehouses são grandes repositórios de dados integrados, construídos para armazenar informações para auxiliar no processo de tomada de decisão. Na Universidade Federal do Paraná, UFPR, foi desenvolvido o projeto SAGU (Sistema de Apoio ao Gerenciamento Universitário), que é um sistema de suporte à decisão, que tem por objetivo prover os administradores daquela universidade com informações que auxiliarão na direção de seus objetivos. O principal componente deste sistema é um data warehouse. Neste artigo nós apresentamos a especificação formal (utilizando Semântica de Ações) do componente Integrador do data warehouse no contexto do projeto SAGU. A especificação obtida foi utilizada para auxiliar no processo de construção do data warehouse e pode ser considerada parte da documentação do projeto de um data warehouse real

    O processo de refrescamento nos sistemas de data warehouse: guião de modelação conceptual da tarefa de extracção de dados

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    Nos últimos anos, os Sistemas de Data Warehouse (SDW) têm sido os sistemas de apoio à decisão mais utilizados nas organizações, integrando dados de diferentes fontes nos Repositórios de Data Warehouse (RDW). Com o decorrer do tempo de funcionamento do sistema, coloca-se o problema do refrescamento, entendido como o problema de assegurar que os conteúdos dos RDW são periodicamente refrescados, de modo a reflectirem as alterações que ocorrem nos dados das fontes que lhes servem de base. Esta dissertação propõe uma abordagem que tem como objectivos principais tornar explícito e documentar o problema do refrescamento e apresentar um guião de modelação conceptual da tarefa de extracção de dados que possa enriquecer as fases subsequentes de desenho para a especificação formal do processo de refrescamento. São dois os contributos desta dissertação. Primeiro, providencia um quadro detalhado sobre o problema do refrescamento que inclui os conceitos e questões fundamentais que permitem caracterizar os SDW, na perspectiva das funcionalidades no apoio à decisão, das abordagens de integração de fontes de dados e dos componentes da arquitectura, os constrangimentos e tarefas que compreendem o processo de refrescamento, as principais abordagens disponíveis na literatura. Segundo, propõe um guião de apoio à modelação conceptual da tarefa de extracção de dados, com base na UML, apresentando os passos que devem ser seguidos pelo designer e disponibilizando as construções que permitem representar os dados que se extraem das fontes, de acordo com as regras que permitem isolar e extrair os dados relevantes para a tomada de decisão.Data Warehouse Systems (DWS) have become very popular in the last years for decision making, by integrating data from internal and external sources into data warehouse stores. As times advances and the sources from which warehouse data is integrated change, the data warehouse contents must be regularly refreshed, such that warehouse data reflect the state of the underlying data sources. This dissertation proposes an approach which main goals are to explicit and document the data warehouse refreshment problem and to present a guidelines for the conceptual modelling of data extraction in order to enrich the subsequent design steps for the formal specification of the refreshment process. The contributions of our approach are twofold. First, it provides a detailed outline of data warehouse refreshment problem, including the main concepts and issues that characterise the general domain of the DWS, such as decision making functionalities, data sources integration approaches and architecture and, the refreshment tasks and constraints as well as the main approaches. Second, it proposes a guidelines for an UML conceptual modelling of data extraction, by giving the sequence of steps for a designer to follow, the modelling constructs for the definition of extracting data, according to the rules that must be accomplished for extracting relevant data

    Formal design of data warehouse and OLAP systems : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems at Massey University, Palmerston North, New Zealand

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    A data warehouse is a single data store, where data from multiple data sources is integrated for online business analytical processing (OLAP) of an entire organisation. The rationale being single and integrated is to ensure a consistent view of the organisational business performance independent from different angels of business perspectives. Due to its wide coverage of subjects, data warehouse design is a highly complex, lengthy and error-prone process. Furthermore, the business analytical tasks change over time, which results in changes in the requirements for the OLAP systems. Thus, data warehouse and OLAP systems are rather dynamic and the design process is continuous. In this thesis, we propose a method that is integrated, formal and application-tailored to overcome the complexity problem, deal with the system dynamics, improve the quality of the system and the chance of success. Our method comprises three important parts: the general ASMs method with types, the application tailored design framework for data warehouse and OLAP, and the schema integration method with a set of provably correct refinement rules. By using the ASM method, we are able to model both data and operations in a uniform conceptual framework, which enables us to design an integrated approach for data warehouse and OLAP design. The freedom given by the ASM method allows us to model the system at an abstract level that is easy to understand for both users and designers. More specifically, the language allows us to use the terms from the user domain not biased by the terms used in computer systems. The pseudo-code like transition rules, which gives the simplest form of operational semantics in ASMs, give the closeness to programming languages for designers to understand. Furthermore, these rules are rooted in mathematics to assist in improving the quality of the system design. By extending the ASMs with types, the modelling language is tailored for data warehouse with the terms that are well developed for data-intensive applications, which makes it easy to model the schema evolution as refinements in the dynamic data warehouse design. By providing the application-tailored design framework, we break down the design complexity by business processes (also called subjects in data warehousing) and design concerns. By designing the data warehouse by subjects, our method resembles Kimball's "bottom-up" approach. However, with the schema integration method, our method resolves the stovepipe issue of the approach. By building up a data warehouse iteratively in an integrated framework, our method not only results in an integrated data warehouse, but also resolves the issues of complexity and delayed ROI (Return On Investment) in Inmon's "top-down" approach. By dealing with the user change requests in the same way as new subjects, and modelling data and operations explicitly in a three-tier architecture, namely the data sources, the data warehouse and the OLAP (online Analytical Processing), our method facilitates dynamic design with system integrity. By introducing a notion of refinement specific to schema evolution, namely schema refinement, for capturing the notion of schema dominance in schema integration, we are able to build a set of correctness-proven refinement rules. By providing the set of refinement rules, we simplify the designers's work in correctness design verification. Nevertheless, we do not aim for a complete set due to the fact that there are many different ways for schema integration, and neither a prescribed way of integration to allow designer favored design. Furthermore, given its °exibility in the process, our method can be extended for new emerging design issues easily
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