The diploma thesis focuses on the present state of Application of Business Intelligence (BI) in Private and Public Sector in the Czech Republic. The first part of this thesis is theoretically oriented and describes the BI evolution, finds its present definition and specifies the relationship to the related fields a branches. There are identified the BI users and there is also described the position of BI in IS/ICT in the organization. After that follows the description of the principles of BI, it means that the components are taken to pieces. The final part shows the possible comprehensive BI solution. The second part is practice-oriented and explores the present state of application of BI in private and public sector and describes the expected BI evolution until 2020. The thesis deals with the potential application of BI and possibilities how to obtain the subsidies from the EU for its implementation in each sector. After that there are described the barriers to implementation of BI and shown some specific examples of significant software solutions in these sectors. Then there are summarized the main differences in application of BI in each sector. The final part focuses on the on-line application research and its evaluation. The diploma thesis shows, why the BI is one of the most perspective business informatics areas. The thesis is also high-quality typographically elaborated.

Made available in DSpace on 2014-06-12T15:55:26Z (GMT). No. of bitstreams: 2 arquivo2236_1.pdf: 2979608 bytes, checksum: 3c3ed256a9de67bd5b716bb15d15cb6c (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / O processo tradicional de descoberta de conhecimento em bases de dados (KDD Knowledge Discovery in Databases) não contempla etapas de processamento multidimensional e multinível (i.e., processamento OLAP - OnLine Analytical Processing) para minerar cubos de dados. Por conseqüência, a maioria das abordagens de OLAM (OLAP Mining) propõe adaptações no algoritmo minerador. Dado que esta abordagem provê uma solução fortemente acoplada ao algoritmo minerador, ela impede que as adaptações para mineração multidimensional e multinível sejam utilizadas com outros algoritmos. Além disto, grande parte das propostas de OLAM para regras de associação não considera o uso de um servidor OLAP e não tira proveito de todo o potencial multidimensional e multinível presentes nos cubos OLAP. Por estes motivos, algum retrabalho (e.g., re-implementação de operações OLAP) é realizado e padrões possivelmente fortes decorrentes de generalizações não são identificados. Diante desse cenário, este trabalho propõe a arquitetura DOLAM (Decoupled OLAM) para mineração desacoplada de regras de associação multidimensional, multinível e de outliers em cubos OLAP. A arquitetura DOLAM deve ser inserida no processo de KDD (Knowledge Discovery in Databases) como uma etapa de processamento que fica entre as etapas de Pré-Processamento e Transformação de Dados. A arquitetura DOLAM define e implementa três componentes: 1) Detector de Outliers, 2) Explorador de Subcubos e 3) Expansor de Ancestrais. A partir de uma consulta do usuário, estes componentes são capazes de, respectivamente: 1) identificar ruídos significativos nas células do resultado; 2) explorar, recursivamente, todas as células do resultado, de forma a contemplar todas as possibilidades de combinações multidimensional e multinível e 3) recuperar todos os antecessores (generalizações) das células do resultado. O componente central da arquitetura é o Expansor de Ancestrais - o único de uso obrigatório. Ressalta-se que, a partir desses componentes, o processamento OLAM fica desacoplado do algoritmo minerador e permite realizar descobertas mais abrangentes, as quais, por conseqüência, podem retornar padrões potencialmente mais fortes. Como prova de conceito, foi realizado um estudo de caso com dados reais de uma empresa de micro-crédito. O estudo de caso foi implementado em Java, fez uso do servidor OLAP Mondrian e utilizou as implementações dos algoritmos para mineração de regras de associação APriori e FP-Growth do pacote de software Weka

Submitted by Lucelia Lucena (lucelia.lucena@ufpe.br) on 2015-03-04T18:33:54Z No. of bitstreams: 2 DISSERTAÇÃO Ana Cecília Vital de Andrade.pdf: 4377501 bytes, checksum: 62069caff1753987554f40017f60aa10 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-04T18:33:54Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO Ana Cecília Vital de Andrade.pdf: 4377501 bytes, checksum: 62069caff1753987554f40017f60aa10 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014-03-14 / SOLAP é uma tecnologia resultante da integração das ferramentas OLAP (Online Analytical Processing) e SIG (Sistemas de Informação Geográfica), cujo objetivo é proporcionar novas possibilidades de análises, uma vez que permite integrar processamento espacial (SIG) e processamento multidimensional-multinível (OLAP) (e.g., qual foi o total de produtos vendidos por loja, cliente, ano, semestre e mês para os clientes que residem até 1km da matriz?). Embora existam muitos trabalhos relacionados à SOLAP, poucos dão atenção à especificação do cliente SOLAP. Neste contexto, ressalta-se que a maioria dos trabalhos existentes apenas dá suporte à manipulação de uma única dimensão espacial e apresentam poucos (algumas vezes nenhum) detalhes sobre a arquitetura e/ou recursos visuais para especificar e sincronizar graficamente operações OLAP e SIG em um cliente SOLAP. Visando propor uma alternativa ao problema descrito, esta dissertação especifica e implementa uma arquitetura de software e uma interface gráfica para um cliente SOLAP Web, o qual visa especificar graficamente operações SOLAP sobre uma ou mais dimensões espaciais, bem como sobre temas externos ao cubo de dados. Como prova de conceito, foi realizado um exemplo de uso do cliente SOLAP construído, que testa a realização de operações SOLAP com as características citadas.

Decision support systems are interactive, computer-based information systems that provide data and analysis tools in order to better assist managers on different levels of organization in the process of decision making. Data warehouses (DWs) have been developed and deployed as an integral part of decision support systems. <p><p>A data warehouse is a database that allows to store high volume of historical data required for analytical purposes. This data is extracted from operational databases, transformed into a coherent whole, and loaded into a DW during the extraction-transformation-loading (ETL) process. <p><p>DW data can be dynamically manipulated using on-line analytical processing (OLAP) systems. DW and OLAP systems rely on a multidimensional model that includes measures, dimensions, and hierarchies. Measures are usually numeric additive values that are used for quantitative evaluation of different aspects about organization. Dimensions provide different analysis perspectives while hierarchies allow to analyze measures on different levels of detail. <p><p>Nevertheless, currently, designers as well as users find difficult to specify multidimensional elements required for analysis. One reason for that is the lack of conceptual models for DW and OLAP system design, which would allow to express data requirements on an abstract level without considering implementation details. Another problem is that many kinds of complex hierarchies arising in real-world situations are not addressed by current DW and OLAP systems.<p><p>In order to help designers to build conceptual models for decision-support systems and to help users in better understanding the data to be analyzed, in this thesis we propose the MultiDimER model - a conceptual model used for representing multidimensional data for DW and OLAP applications. Our model is mainly based on the existing ER constructs, for example, entity types, attributes, relationship types with their usual semantics, allowing to represent the common concepts of dimensions, hierarchies, and measures. It also includes a conceptual classification of different kinds of hierarchies existing in real-world situations and proposes graphical notations for them.<p><p>On the other hand, currently users of DW and OLAP systems demand also the inclusion of spatial data, visualization of which allows to reveal patterns that are difficult to discover otherwise. The advantage of using spatial data in the analysis process is widely recognized since it allows to reveal patterns that are difficult to discover otherwise. <p><p>However, although DWs typically include a spatial or a location dimension, this dimension is usually represented in an alphanumeric format. Furthermore, there is still a lack of a systematic study that analyze the inclusion as well as the management of hierarchies and measures that are represented using spatial data. <p><p>With the aim of satisfying the growing requirements of decision-making users, we extend the MultiDimER model by allowing to include spatial data in the different elements composing the multidimensional model. The novelty of our contribution lays in the fact that a multidimensional model is seldom used for representing spatial data. To succeed with our proposal, we applied the research achievements in the field of spatial databases to the specific features of a multidimensional model. The spatial extension of a multidimensional model raises several issues, to which we refer in this thesis, such as the influence of different topological relationships between spatial objects forming a hierarchy on the procedures required for measure aggregations, aggregations of spatial measures, the inclusion of spatial measures without the presence of spatial dimensions, among others. <p><p>Moreover, one of the important characteristics of multidimensional models is the presence of a time dimension for keeping track of changes in measures. However, this dimension cannot be used to model changes in other dimensions. <p>Therefore, usual multidimensional models are not symmetric in the way of representing changes for measures and dimensions. Further, there is still a lack of analysis indicating which concepts already developed for providing temporal support in conventional databases can be applied and be useful for different elements composing a multidimensional model. <p><p>In order to handle in a similar manner temporal changes to all elements of a multidimensional model, we introduce a temporal extension for the MultiDimER model. This extension is based on the research in the area of temporal databases, which have been successfully used for modeling time-varying information for several decades. We propose the inclusion of different temporal types, such as valid and transaction time, which are obtained from source systems, in addition to the DW loading time generated in DWs. We use this temporal support for a conceptual representation of time-varying dimensions, hierarchies, and measures. We also refer to specific constraints that should be imposed on time-varying hierarchies and to the problem of handling multiple time granularities between source systems and DWs. <p><p>Furthermore, the design of DWs is not an easy task. It requires to consider all phases from the requirements specification to the final implementation including the ETL process. It should also take into account that the inclusion of different data items in a DW depends on both, users' needs and data availability in source systems. However, currently, designers must rely on their experience due to the lack of a methodological framework that considers above-mentioned aspects. <p><p>In order to assist developers during the DW design process, we propose a methodology for the design of conventional, spatial, and temporal DWs. We refer to different phases, such as requirements specification, conceptual, logical, and physical modeling. We include three different methods for requirements specification depending on whether users, operational data sources, or both are the driving force in the process of requirement gathering. We show how each method leads to the creation of a conceptual multidimensional model. We also present logical and physical design phases that refer to DW structures and the ETL process.<p><p>To ensure the correctness of the proposed conceptual models, i.e. with conventional data, with the spatial data, and with time-varying data, we formally define them providing their syntax and semantics. With the aim of assessing the usability of our conceptual model including representation of different kinds of hierarchies as well as spatial and temporal support, we present real-world examples. Pursuing the goal that the proposed conceptual solutions can be implemented, we include their logical representations using relational and object-relational databases.<p> / Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

With the ascendency of data and the rise of interest in analytics, organizations are becoming more interested in the use of data to make their business processes more intelligent and reactive. BI applications are a common way that organizations integrate analytics in their processes. However, it can be days, weeks or even months before a manual response is undertaken based on a human interpreting a report. Even when information technology supports automatic responses within an organization, it is often implemented in an ad hoc manner without following a systematic framework. In this thesis, we present a reactive performance monitoring (RPM) framework which aims at automating the link from the analytical (how well is the operational achieving the strategic) to the operational (the particular process steps implemented within an organization that determine its behavior) aspects of businesses to bypass the strategic (the high level and long term goals an organization is trying to achieve) as needed and reduce the latency between knowledge and action. Our RPM framework is composed of an architecture, a methodology, and a rule environment which permits the redaction of rules possessing relevant conditions and actions. In addition, we present an OLAP rule engine which is demonstrated to be effective in our framework where events are streamed in, reacted upon in real-time, and stored in an OLAP database. To develop and evaluate our framework, two case studies were undertaken. The first was done using IBM technologies implementing an application made to identify patients at high risk of cancer recurrence. The second was done using open source technologies. With this second implementation, we created an application that has the goal of informing women from at risk populations of the different stages of pregnancy on a weekly basis.

Cílem této práce je porovnání komerčních business intelligence nástrojů s nástroji Open Source v procesu implementace BI řešení ve střední firmě. V práci jsou porovnávány komerční aplikace Oracle (http://www.oracle.com) ? Oracle Warehouse Builder, Oracle Discoverer a Open Source nástroje z projektu Pentaho (http://www.pentaho.com) ? Kettle, Cube Designer a BI Platforma. Hodnocení obou systémů probíhá na základě předem definovaných metrik. Práce kromě popisu realizace obou řešení a jejich vzájemného porovnání také dává odpověď na zcela zásadní otázku, zda může Open Source řešení konkurovat tomu komerčnímu. Dalším přínosem je návrh modifikovatelného a znovupoužitelného stromu metrik, který je k hodnocení systémů použit.

This diploma thesis deals with an analysis of SAP Business Intelligence platform (SAP NetWeaver BI 7.0) and compares its chosen tools with Microsoft SQL Server BI. The main aim of the thesis is to evaluate SAP BI system in a comprehensive way whereas extra attention is paid to certain areas, such as a data warehouse. One of the goals is the comparison of approaches and methods of the creation of the data warehouse with MS SQL Server BI solution. The thesis consists of theoretical insight into Business Intelligence, which is focused on the architecture of data warehouse, and OLAP technologies. There is an evaluation of the role of SAP in the BI market followed by the introduction of SAP NetWeaver, an application and integration platform. Included is also an analysis of the architecture of data warehouse, methods of storing data, ETL process and other chosen functions and tools (including presentation tools) in next sections. A sample application in the final part provides the reader with better understanding of different ETL approaches, which are analyzed into detail and evaluated. There is the comparison of OLAP technologies in the end and the comparison of basic reporting tools, as well.

Currently, Business Intelligence has a very solid position in the enterprise information systems' market. However, there is no unified approach to the evaluation of effects of these solutions in the enterprise. It is a common practice that the transmission of the accepted solution automatically means successful completion of the development project, causing a gradual decrease in the supplier's interest of the users' satisfaction with this solution. This thesis deals with the problem of evaluating the success of custom Business Intelligence solutions. The main objective of this work is a new perspective on the issue of users' satisfaction and create a generally applicable concept for its evaluation. This objective will be achieved on the basis of a comprehensive theoretical analysis of effects of these solutions with the reasons why the work focuses on the analysis of users. It presents a total of two methods for evaluating the users' satisfaction of reporting solutions from the users. In order to demonstrate the viability of this concept, the two methods will be applied in practical part to a specific BI solution, including the demonstration of achieved results and assessing the suitability of both methods. This section is based on the experience of the real project.

The need for reliable and exact information that are needed to run a company is still growing. This fact leads to finding new ways to obtain, transform, but especially deliver these information. One of the most efficient way is to integrate Business Intelligence into company's information system that leads to the usage of analytical portals. This thesis's target is to acquaint the readers with the topic of analytical portals and conceivable method to evaluate analytical portals and tools designed to build them. This thesis consists of two general sections, theoretical and practical. The theoretical section consists of the explanation of the term analytical portal and the ways a company can benefit from usage of analytical portals. The criteria and the conceivable method to evaluate analytical portals and the tools designed to build them are specified further in this section. The practical section contains description and evaluation of certain tool designed to build analytical portals (SAS Portal). The evaluation is based on the criteria described in the theoretical section and data used in the exhibition of the SAS Portal are purely exemplificative.

This thesis is focused on topics of Business Intelligence, Balanced Scorecard and its implementation in agricultural company Novak Co. Both methods will be applied to section warehouse of spare parts. Warehouse by Novak Co. deals with provision of spare parts for own consumption and sale of spare parts to external customers. The thesis consists of theoretical and practical parts. Theoretical part deals with a description of essential ideas of BSC and BI. Practical part deals with examination of gained knowledge by implementation BSC and BI to warehouse by Novak Co.. To begin with, the first chapter is focused on Balanced Scorecard methodology. There is a description of principles BSC, description of company goals via four perspectives and the definition of strategic map. There are described basic principles of BI, multidimensionality, main components of BI application and a few definitions of BI from different sources in the second charter. In theoretical part, there are mentioned a few thesis, which deals with the same or similar subject, like this thesis. The practical part is focused on design of pilot project of BI solution for the warehouse of spare parts in the company Novak Co.. At first there was processed the analysis of BSC and the analysis of accessible resources in order to determine possibilities and requests for BI application. Based on requests there is designed the data warehouse, ETL tools and OLAP cubes. Reporting is carried out by MS Excel 2007. The Outputs of BI application are based on real company's requests. The main benefit of this thesis is to demonstrate the usability of BI tools and BSC methodology in section of warehouse of spare parts.