Made available in DSpace on 2015-04-14T14:48:56Z (GMT). No. of bitstreams: 1 399886.pdf: 1933710 bytes, checksum: 802b7870cad99de8d93c140653277d3d (MD5) Previous issue date: 2007-12-21 / A busca pela qualidade ? uma constante nos ambientes corporativos. Para tanto, as opera??es de desenvolvimento de software utilizam m?tricas para mensurar a qualidade dos seus produtos, processos e servi?os. As mesmas devem ser coletadas, consolidadas e armazenadas em um reposit?rio central ?nico, tipicamente implementado na forma de Data Warehouse (DW). A defini??o do processo de extra??o, transforma??o e carga (ETC) das m?tricas a serem armazenadas nesse reposit?rio, considerando as caracter?sticas do ambiente de desenvolvimento de software (heterogeneidade de fontes, de modelos de processos, de tipos de projetos e de n?veis de isolamento) n?o ? uma tarefa trivial. Este trabalho apresenta um ambiente de data warehousing denominado SPDW+, como solu??o para a automatiza??o do processo de ETC das m?tricas. Esta solu??o cont?m um modelo anal?tico abrangente e elegante, para an?lise e monitora??o de m?tricas, e ? baseada em uma abordagem orientada a servi?os, aliada ? tecnologia de Web Services (WS). Al?m disso, o SPDW+ trata a carga incremental com baixo n?vel de intrus?o, e alta freq??ncia e baixa lat?ncia na coleta das m?tricas. Os principais componentes da solu??o s?o especificados, implementados e testados. Os benef?cios desta solu??o s?o: i) ser flex?vel e adapt?vel para atender ?s constantes modifica??es do ambiente do neg?cio; ii) oferecer suporte ? monitora??o, permitindo a realiza??o de cargas freq?entes e incrementais; iii) ser capaz de desonerar os projetos da tarefa, laboriosa e complexa, de captura das m?tricas; iv) manter a liberdade de escolha dos projetos, quanto aos modelos de gest?o e ?s ferramentas de apoio empregadas; e v) possibilitar que as informa??es contidas no reposit?rio de m?tricas estejam coesas e consistentes, para que os dados de diferentes projetos sejam compar?veis entre si.

Made available in DSpace on 2015-04-14T14:49:43Z (GMT). No. of bitstreams: 1 437994.pdf: 1640213 bytes, checksum: 26f32168808fae3383c6bd3a3b9c87fc (MD5) Previous issue date: 2010-03-30 / Organizations acting on several markets have been using the benefits offered by the use of Data Mining - DM techniques as a complementary activity to their support systems to the strategic decision. However, to the great majority of the organizations, the deployment of a DM Project ends up not being feasible due to different factors, such as: Project duration, high costs and mainly by the uncertainty as to getting results that may effectively help the organization to improve their business processes. In this context, this paper presents a process based on the process of knowledge Discovery in Database - KDD which aims to identify opportunities to the application of DM techniques through the induction and ranking of decisions generated by the exploration of semi automatic Online Analytical Processing Models-OLAP. The built process uses stored information in a OLAP model prepared on the basis of used information by Customer Relationship Management - CRM and Business Intelligence - BI typically used by the organization to support strategic decision making. In relation to the information selected for this research, it has been carried out in a semi automatic way, a series of experiments using DM techniques which the results are collected and stored for later evaluation and ranking. The process was built and tested with a significant number of experiments and later evaluated by business experts in a large financial institution where this research was developed. / Organiza??es atuantes nos mais diferentes mercados, t?m utilizado os benef?cios oferecidos pela utiliza??o de t?cnicas de Data Mining DM como atividades complementares a seus sistemas de apoio a decis?o estrat?gica. Por?m, para a grande maioria das organiza??es, a implanta??o de um projeto de DM acaba sendo inviabilizada em fun??o de diferentes fatores como: dura??o do projeto, custos elevados e principalmente pela incerteza quanto ? obten??o de resultados que possam auxiliar de fato a organiza??o a melhorar seus processos de neg?cio. Neste contexto, este trabalho apresenta um processo, baseado no processo de Knowledge Discovery in Database KDD, que visa identificar oportunidades para aplica??o de t?cnicas de DM atrav?s da indu??o e ranqueamento de ?rvores de decis?o geradas pela explora??o semiautom?tica de modelos On-Line Analytical Processing - OLAP. O processo constru?do utiliza informa??es armazenadas em um modelo OLAP preparado com base nas informa??es utilizadas por sistemas de Customer Relationship Management - CRM e Business Intelligence BI, tipicamente utilizados por organiza??es no apoio a tomada de decis?o estrat?gica. Neste trabalho ? apresentada uma s?rie de experimentos, gerados de forma semiautom?tica, utilizando t?cnicas de DM, cujos resultados s?o coletados e armazenados para posterior avalia??o e ranqueamento. O processo foi constru?do e testado com um conjunto significativo de experimentos e posteriormente avaliado por especialistas de neg?cio em uma institui??o financeira de grande porte onde esta pesquisa foi desenvolvida.

Les systèmes d’aide à la décision occupent une place prépondérante au sein des entreprises et des grandes organisations, pour permettre des analyses dédiées à la prise de décisions. Avec l’avènement du big data, le volume des données d’analyses atteint des tailles critiques, défiant les approches classiques d’entreposage de données, dont les solutions actuelles reposent principalement sur des bases de données R-OLAP. Avec l’apparition des grandes plateformes Web telles que Google, Facebook, Twitter, Amazon… des solutions pour gérer les mégadonnées (Big Data) ont été développées et appelées « Not Only SQL ». Ces nouvelles approches constituent une voie intéressante pour la construction des entrepôts de données multidimensionnelles capables de supporter des grandes masses de données. La remise en cause de l’approche R-OLAP nécessite de revisiter les principes de la modélisation des entrepôts de données multidimensionnelles. Dans ce manuscrit, nous avons proposé des processus d’implantation des entrepôts de données multidimensionnelles avec les modèles NoSQL. Nous avons défini quatre processus pour chacun des deux modèles NoSQL orienté colonnes et orienté documents. De plus, le contexte NoSQL rend également plus complexe le calcul efficace de pré-agrégats qui sont habituellement mis en place dans le contexte ROLAP (treillis). Nous avons élargis nos processus d’implantations pour prendre en compte la construction du treillis dans les deux modèles retenus.Comme il est difficile de choisir une seule implantation NoSQL supportant efficacement tous les traitements applicables, nous avons proposé deux processus de traductions, le premier concerne des processus intra-modèles, c’est-à-dire des règles de passage d’une implantation à une autre implantation du même modèle logique NoSQL, tandis que le second processus définit les règles de transformation d’une implantation d’un modèle logique vers une autre implantation d’un autre modèle logique. / Decision support systems occupy a large space in companies and large organizations in order to enable analyzes dedicated to decision making. With the advent of big data, the volume of analyzed data reaches critical sizes, challenging conventional approaches to data warehousing, for which current solutions are mainly based on R-OLAP databases. With the emergence of major Web platforms such as Google, Facebook, Twitter, Amazon...etc, many solutions to process big data are developed and called "Not Only SQL". These new approaches are an interesting attempt to build multidimensional data warehouse capable of handling large volumes of data. The questioning of the R-OLAP approach requires revisiting the principles of modeling multidimensional data warehouses.In this manuscript, we proposed implementation processes of multidimensional data warehouses with NoSQL models. We defined four processes for each model; an oriented NoSQL column model and an oriented documents model. Each of these processes fosters a specific treatment. Moreover, the NoSQL context adds complexity to the computation of effective pre-aggregates that are typically set up within the ROLAP context (lattice). We have enlarged our implementations processes to take into account the construction of the lattice in both detained models.As it is difficult to choose a single NoSQL implementation that supports effectively all the applicable treatments, we proposed two translation processes. While the first one concerns intra-models processes, i.e., pass rules from an implementation to another of the same NoSQL logic model, the second process defines the transformation rules of a logic model implementation to another implementation on another logic model.

Diploma thesis focuses on topic of business performance management realized through Business Intelligence application created on the basis of a balanced set of indicators within the Balanced Scorecard method. The first part introduces the reader with theoretical foundations. First, it describes the basic principles of the BSC method and meaning of dividing strategic objectives into four perspectives. Subsequently, it introduces the heart of BI - a multidimensional approach, displays the BI architecture and defines its components. At the end it compares the types of database systems. There is also a comparison of this thesis with other projects dealing with similar themes in the theoretical part. After the theoretical chapters comes a practical part which aims at design and development of BI applications for a real company so as to comply with the requirements of top managers and the corporate strategy. At the beginning it introduces a firm to which the project is applied. This is an existing organization operating in the area of car sales and services. The corporation is called under a fictitious name "AUTO a.s." in this thesis. In cooperation with its managers the SWOT analysis and strategic objectives is defined. This determines the key requirements for setting up the BI application. An example of a BI solution that allows managers to effectively monitor the development objectives, brings the main benefit of the whole work. For this purpose is built data warehouse, which is then filled with transformed data from source systems using Data Pump. Then, above the Data Warehouse, two OLAP cubes can be created. Presentation layer, created in MS Excel 2007, handles the interpretation of the results to end-users.

隨著網際網路的發達以及資料庫技術的成熟，人們取得資料變得非常的容易，再加上許多網際網路的應用其實就是一個自動化的資料收集工具，資料量之大已幾近爆炸的程度。資料倉儲便是一種用來儲存大量歷史資料的資料庫，提供彙整或是統計的資訊，以提供決策使用的資訊技術。而資料探勘是從大量的資料當中把對於決策過程中有幫助的規則找出來，提供給管理人員做為決策的參考，開創新的商業契機。資料倉儲的效能表現對於使用者的工作效率有著深遠的影響。因此有些用以衡量與預測資料倉儲之效能與效率之工作量模式便孕育而生，一般稱之為績效評估工具，然而目前所公佈的一般資料倉儲績效評估工具是針對特定範圍領域建構出某些典型的領域規格，並沒有一個使用者需求導向的資料倉儲績效評估工具。在資料探勘方面，探勘結果的準確度比起資料探勘所花費的時間來得重要，目前卻沒有一個有效、使用者需求導向的工具來評估資料探勘結果的準確度。我們針對資料倉儲的效能評估以及資料探勘準確度評估，設計一個以使用者需求為導向的工作量模型，來評估資料倉儲與資料探勘工具。 / As growth of Internet and mature of database technology, people can get the data much easily than before. Many applications on Internet, in fact, are the tools of gather data automatically so that the amount of data is growing bigger and bigger. Data warehouse is one kind of database to store lots of historical data to offer statistical information for the information technology of decisions. Data mining is to find the useful rules for decisions from the amount of data to help the managers make decisions and create the new opportunities of business. The performance of data warehouse is import to user’s work efficiency. Therefore, there are some workload model arise to evaluate and predict the performance and efficiency of data warehouse called benchmark. However, the data warehouse specification announced these days are constructed to some typical domain specific, and the performance evaluation stand on synthetic workload. But, when the difference between the domain of data warehouse user applied and domain of performance evaluation tool is very large, the performance metric may different a lot to the result of benchmark tool. In data mining, the accuracy of mining result is important to business. The accuracy of mining result is more important than the time spend on data mining. However, there is no any useful tool to evaluate the accuracy of mining result and there is no any standard of performance criteria for data mining, either. We design a user requirement-oriented workload to evaluate performance of data warehouse and precision of data mining.

Tai darbas apie duomenų saugyklos ir OLAP galimybių panaudojimą skaitmeninės antžeminės televizijos paslaugos pardavimo procese. Atlikta išsami probleminės srities analizė, duomenų saugyklos, integravimo, kubų projektavimas ir realizavimas. Darbas atliktas, pasinaudojant MS SQL Server 2005 analizavimo ir integravimo paslaugomis. / This master`s work investigates data warehouse and OLAP tools opportunities research and practical use in organization which produces DVB-T (digital video broadcasting terrestrial) service for end-users. This work consist of problem analysis, data warehouse, data integration, data cubes project and realization. Realization was done using Ms SQL Server 2005 analysis and integration services.

提供以顧客為導向的服務、提升顧客價值成為各企業經營策略的出發點，因此了解顧客特徵、需求、行為成為首要任務。 隨著經濟發展，台灣整體用電需求不斷攀升，同時電力產業亦須面對全球燃料價格上漲的現況，政府邁向低碳經濟時代，推出一系列相關政策，於我國電力結構中占有重要地位的台灣電力公司也開始思考如何在需求及成本皆提升的環境下，繼續維持穩定供電，提供以用戶為導向的服務。 本文即以台電公司為個案，以資料倉儲與資料採礦技術進行【用戶區隔】了解台電用戶特徵、【選擇目標用戶】找出優先服務的用戶對象及【產品定位】推薦適合目標用戶用電特徵之電價及優惠方案，實現行銷活動STP分析過程之研究。 / Providing customer-oriented services and elevating customer value have became the starting point of business strategy. Therefore, understanding customer characteristics, requirements, and behavior has become the primary task. As the overall demand for electricity rises constantly in Taiwan along with economic development, electric power industries have to face the surging fuel prices. To put low carbon economy into practice, the government has launched various policies. Taiwan Power Company, which plays an important role in the electric power structure in Taiwan, started thinking about how to provide stable power and customer-oriented services under the circumstances both demand and cost increase. Based on the case of Taiwan Power Company, this research investigated customer segmentation - to understand customer characteristic, customer targeting - to find out the prior customer, and product positioning - to recommend target customer appropriate tariff and preferential tariff treatment through data warehouse and data mining technology. The purpose of the research was to achieve STP analysis in marketing process.

This diploma thesis deals with the management of information flow of a small company using Business Intelligence tools and the data mart. There is defined the problem of working with information from the point of view of selected company in the first part. The next part presents selected theoretical background on the basis of which was the aim achieved. The fourth part analyses the current situation of the company. There is recommended complex improvement of the current situation in the practical part. Selected information management problem is accomplished factually. There are also introduced suitable software tools, which were used for the solution.

This study considers the details of development and use of a model of the visualization process to transform data in a warehouse to required insight. In the context of this study, `visualization process' refers to a step-wise methodology to develop enhanced insight by using visualization techniques. The model, named RoutePlanner, was developed by the researcher from a theoretical perspective and was then used and evaluated practically in the domain of insurance brokerage. The study highlights the proposed model, which comprises stages for the identification of the relevant data, selection of visualization methods and evaluation of the visualizations, undergirded by a set of practical guidelines. To determine the effect of the use of RoutePlanner an experiment was conducted to test a theory. The practical utility of RoutePlanner was assessed during an evaluation-of-use study. The goal of this study is to present the RoutePlanner model and the effect of its use. / Theoretical Computing / M.Sc. (Information Systems)

LEAL, Bruno de Carvalho. Da modelagem Conceitual à Representação Lógica de Trajetórias em SGBDOR e Sistemas de DW. 2011. 120 f. : Dissertação (mestrado) - Universidade Federal do Ceará, Centro de Ciências, Departamento de Computação, Fortaleza-CE, 2011. / Submitted by guaracy araujo (guaraa3355@gmail.com) on 2016-06-03T18:06:29Z No. of bitstreams: 1 2011_dis_bcleal.pdf: 2151043 bytes, checksum: 6cb423b35ccbf999cc937ddda41507be (MD5) / Approved for entry into archive by guaracy araujo (guaraa3355@gmail.com) on 2016-06-03T18:07:43Z (GMT) No. of bitstreams: 1 2011_dis_bcleal.pdf: 2151043 bytes, checksum: 6cb423b35ccbf999cc937ddda41507be (MD5) / Made available in DSpace on 2016-06-03T18:07:43Z (GMT). No. of bitstreams: 1 2011_dis_bcleal.pdf: 2151043 bytes, checksum: 6cb423b35ccbf999cc937ddda41507be (MD5) Previous issue date: 2011 / Com o aumento do número de dispositivos móveis equipados com serviços de localização geográfica, tem se tornado cada vez mais economicamente e tecnicamente possível capturar os percursos (i.e. trajetórias) dos objetos móveis. Muitas aplicações interessantes têm sido desenvolvida com intuito de explorar análises de trajetórias de objetos móveis. Por exemplo, em sistemas de gerenciamento de veículos de entrega, pode ser realizado tanto o monitoramento dos veículos quanto análises para apoio a decisões estratégicas. De modo geral, as trajetórias podem ser analisadas em duas perspectivas: tempo real e histórica. Além disso, aplicações de trajetórias compartilham uma necessidade em comum que é o registro mais estruturado do movimento. Isso permite manipular trajetórias como objetos de primeira classe e adicionar qualquer semântica requerida pela aplicação e, também, a criação de métodos robustos e eficientes para agregar conjuntos de trajetórias de forma a permitir a realização de análises complexas. Este trabalho estende um trabalho anterior na modelagem conceitual de trajetórias pela generalização da ideia de paradas e movimentos e pela definição de um conjunto de funções de agregação para trajetórias. Neste trabalho é proposto, ainda, duas abordagens por modelagem, ambas baseadas em meta-esquemas, para elaboração de esquemas de trajetórias para ambiente transacional e multidimensional. Para demonstrar e provar nossas contribuições apresentamos um caso de estudo real sobre trajetórias de caminhões de entrega. Os resultados experimentais demonstram que as abordagens de modelagem oferecem a flexibilidade necessária para lidar com a complexidade da semântica das trajetórias em análises de tempo real e histórica.