On-line analytical processing (OLAP) provides multidimensional data analysis to support decision making. OLAP queries require extensive computation based on aggregation along many dimensions and hierarchies. The time required to process these queries has traditionally prevented the interactive analysis of large databases and in order to accelerate query-response time, precomputed results are often stored as materialised views for later retrieval. This adds a prohibitive storage overhead when applied to the whole set of aggregates, known as the data cube. Storage space and computation time can be significantly reduced by partial computation. The challenge in implementing the data cube has been to select the minimum number of views for materialisation, while retaining fast query response time. This thesis makes significant contributions to this area by introducing the Low Redundancy (L-R) approach which provides the means for the selection, computation and storage of nonredu ndant aggregates. Firstly, through the introduction of a novel technique, redundant aggregates are identified thus allowing only distinct aggregates to be computed and stored. Secondly, further redundancy is identified and eliminated using a second novel technique which stores these distinct aggregates in a compact differential form. Novel algorithms were introduced to implement these techniques and provide a solution which is both scalable and low in complexity. Both techniques have been evaluated using real and synthetic datasets with experimental results, and have achieved significant savings in computation time and storage space compared to the conventional approach. Savings have been shown to increase as dimensionality increases. Existing techniques for implementing the data cube differ from the L-R approach but they can be integrated with it to achieve faster query-response time. Finally, the implications of this work reach beyond the area of OLAP to the fields of decision support systems, user interfaces and data mining.

Due to the increasing global competition in today¡¦s business environment, current Transaction Processing Systems and Management Information Systems can no longer satisfy the enterprise¡¦s needs. Mangers need to analyze data from different views to recognizing business status, making decisions, and setting up the policies. To support such works, many information systems and technologies are developed including Decision Support Systems, Executive Information Systems, data warehouses, and On-Line Analytical Processing (OLAP). The implementation of OLAP and data warehousing project are expensive and risky. The results of implementing OLAP and data warehousing in most of the organizations do not, however, always prove a success. The common problem occurs in the requirement analysis phase when analyzing the dimensions and hierarchical relationships for OLAP. The user requirement can not be defined completely and the developers often need to modify or reconstruct the dimensions and hierarchical relationships to meet the user¡¦s changing needs. This is an enormous burden to the system developers. Although many tools with OLAP provide the flexibility for user creating analytical reports by using predefined dimensions and hierarchical relationships. However, a methodology for designing flexible report for OLAP to support ad hoc analysis is still lacking. This study proposes a methodology that is developed for designing flexible report for OLAP, which presents the dimensions and hierarchical relationships by visualized meta-templates and templates to help users create analysis reports. The methodology provides the flexibility not only in representing dimensions and hierarchical relationships for OLAP, but also in producing flexible reports. With such flexibility, the users can create analytical reports to support ad hoc analysis by choosing appropriated meta-template and template easily.

ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / This paper is a follow on to a paper presented at the 2005 International Telemetry Conference by Dr. Samuel Harley et. al., titled Data, Information, and Knowledge Management. This paper will describe new techniques and provide further detail into the inner workings of the VISION (Versatile Information System – Integrated, Online) Engineering Performance Data Mart.

No description available.

Tor is a distributed network providing privacy and anonymity on the Internet. Information about Tor is publicly available in a form of consensus documents. Existing tools that are able to display this information do not provide both historical and detailed view of it. A tool named Consensus Parser that provides a detailed, historical view of this information and extends it with geolocation and DNS information, was created as a part of TARZAN research project at Brno University of Technology. It stores the information in regular files on disk and makes it accessible via REST API. This thesis extends Consensus Parser with MariaDB ColumnStore database with a schema designed to conform to OLAP needs. The searching capabilities of Consensus Parser were enhanced by adding 109 new endpoints to 12 existing ones and adding the ability to limit the retrieved information to certain fields only. Disk space needed for storing the information was reduced by a factor of five.

Este trabalho trata da especificação, desenvolvimento e utilização do Sistema de Apoio à Gestão de Utilidades e Energia - SAGUE, um sistema concebido para auxiliar na análise de dados coletados de sistemas de utilidades como ar comprimido, vapor, sistemas de bombeamento, sistemas para condicionamento ambiental e outros, integrados com medições de energia e variáveis climáticas. O SAGUE foi desenvolvido segundo conceitos presentes em sistemas de apoio à decisão como Data Warehouse e OLAP - Online Analytical Processing - com o intuito de transformar os dados oriundos de medições em informações que orientem diretamente as ações de conservação e uso racional de energia. As principais características destes sistemas, que influenciaram na especificação e desenvolvimento do SAGUE, são tratadas neste trabalho. Além disso, este texto aborda a gestão energética e os sistemas de gerenciamento de energia visando apresentar o ambiente que motivou o desenvolvimento do SAGUE. Neste contexto, é apresentado o Sistema de Gerenciamento de Energia Elétrica - SISGEN, um sistema de informação para suporte à gestão de energia elétrica e de contratos de fornecimento, cujos dados coletados podem ser analisados através do SAGUE. A aplicação do SAGUE é tratada na forma de um estudo de caso no qual se analisa a correlação existente entre o consumo de energia elétrica da CUASO - Cidade Universitária Armando de Sales Oliveira, obtido através do SISGEN, e as medições de temperatura ambiente, fornecidas pelo IAG - Instituto de Astronomia, Geofísica e Ciências Atmosféricas da USP. / This work deals with specification, development and utilization of the Support System for Utility and Energy Management - SAGUE, a system created to assist in analysis of data collected from utilities systems as compressed air, vapor, water pumping systems, environmental conditioning systems and others, integrated with energy consumption and climatic measurements. The development of SAGUE was based on concepts and methodologies from Decision Support System as Data Warehouse and OLAP - Online Analytical Processing - in order to transform data measurements in information that guide the actions for energy conservation and rational utilization. The main characteristics of Data Warehouse and OLAP tools that influenced in the specifications and development of SAGUE are described in this work. In addition, this text deals with power management and energy management systems in order to present the environment that motivated the SAGUE development. Within this context, it is presented the Electrical Energy Management System - SISGEN, a system for energy management support, whose electrical measurements can be analyzed by SAGUE. The SAGUE utilization is presented in a case study that discusses the relation between electrical energy consumption of CUASO - Cidade Universitária Armando de Sales Oliveira, obtained throughout SISGEN, and the local temperature measurements supplied by IAG - Institute of Astronomic and Atmospheric Science of USP.

Nesta dissertação são feitas três abordagens. Na primeira apresentam-se os componentes necessários para que se possa compreender melhor o cenário atual onde se encontram aqueles que são os responsáveis pelo processo decisório nas empresas. São abordados as evoluções do processo decisório e do suporte ao mesmo, suas etapas e os seus fatores de influência. A segunda abordagem é relativa às três ferramentas que constituem a nova geração de Sistemas de Apoio à Decisão. A primeira ferramenta é o data warehouse, um banco de dados específico para propósitos gerenciais e que é independente dos bancos de dados operacionais. A segunda ferramenta é o On-Line Analytical Processing (OLAP) e é utilizada para se realizar análises sofisticadas, que permitem aos seus usuários compreenderem melhor os negócios que são realizados na empresa. A última ferramenta é o data mining que permite que se faça uma análise nos dados armazenados, durante anos, para que se descubram relacionamentos ocultos entres os dados, revelando perfis de compras e de clientes; desta forma, as informações obtidas podem se tornar estratégias de negócios. Com a abordagem destas três novas ferramentas, deseja-se analisar o que existe de mais avançado, atualmente, para dar um melhor suporte ao processo decisório, sem entrar nos detalhes estritamente técnicos destas tecnologias. A terceira abordagem é constituída de exemplos de empresas que implementaram estas ferramentas e os resultados obtidos, assim como pelas tendências destas ferramentas para os próximos anos. / In this dissertation we will deal with three approaches. On the first we present the necessary elements to make one understand better the current scenery where the responsible persons for the decision process of companies meet. The evolution of the decision process and its support, phases and influence factors. The second approach is related to the three tools that constitute the new generation of Decision Support Systems. The first tool is the data warehouse, a specific database for the managerial purposes that is independent from the operational databases. The second tool is the On-Line Analytical Processing (OLAP) used in carrying out sophisticated analyses allowing its users a better understanding of the business accomplished in the company. The last tool is the data mining that allows for an analysis of the data stored along the years so that one is able to find out the correct relationship among the collect’s data, revealing business and clients profiles. In such way all the information gathered in the process can be converted into business strategy. With the approach of these three new tools we intend to analyze the most advanced techniques available nowadays to give a better decision support without getting into strictly technical details of these technologies. The third approach is made up of examples of companies that implemented such tools and the attained results, as well, the trends for these tools in the coming years.

L'analyse en ligne OLAP (Online Analytical Processing) est une des technologies les plus importantes dans les entrepôts de données, elle permet l'analyse multidimensionnelle de données. Cela correspond à un outil d'analyse puissant, tout en étant flexible en terme d'utilisation pour naviguer dans les données, plus ou moins en profondeur. OLAP a été le sujet de différentes améliorations et extensions, avec sans cesse de nouveaux problèmes en lien avec le domaine et les données, par exemple le multimedia, les données spatiales, les données séquentielles, etc. A l'origine, OLAP a été introduit pour analyser des données structurées que l'on peut qualifier de classiques. Cependant, l'émergence des réseaux d'information induit alors un nouveau domaine intéressant qu'il convient d'explorer. Extraire des connaissances à partir de larges réseaux constitue une tâche complexe et non évidente. Ainsi, l'analyse OLAP peut être une bonne alternative pour observer les données avec certains points de vue. Différents types de réseaux d'information peuvent aider les utilisateurs dans différentes activités, en fonction de différents domaines. Ici, nous focalisons notre attention sur les réseaux d'informations bibliographiques construits à partir des bases de données bibliographiques. Ces données permettent d'analyser non seulement la production scientifique, mais également les collaborations entre auteurs. Il existe différents travaux qui proposent d'avoir recours aux technologies OLAP pour les réseaux d'information, nommé ``graph OLAP". Beaucoup de techniques se basent sur ce qu'on peut appeler cube de graphes. Dans cette thèse, nous proposons une nouvelle approche de “graph OLAP” que nous appelons “Graphes enrichis par des Cubes” (GreC). Notre proposition consiste à enrichir les graphes avec des cubes plutôt que de construire des cubes de graphes. En effet, les noeuds et/ou les arêtes du réseau considéré sont décrits par des cubes de données. Cela permet des analyses intéressantes pour l'utilisateur qui peut naviguer au sein d'un graphe enrichi de cubes selon différents niveaux d'analyse, avec des opérateurs dédiés. En outre, notons quatre principaux aspects dans GreC. Premièrement, GreC considère la structure du réseau afin de permettre des opérations OLAP topologiques, et pas seulement des opérations OLAP classiques et informationnelles. Deuxièmement, GreC propose une vision globale du graphe avec des informations multidimensionnelles. Troisièmement, le problème de dimension à évolution lente est pris en charge dans le cadre de l'exploration du réseau. Quatrièmement, et dernièrement, GreC permet l'analyse de données avec une évolution du réseau parce que notre approche permet d'observer la dynamique à travers la dimension temporelle qui peut être présente dans les cubes pour la description des noeuds et/ou arêtes. Pour évaluer GreC, nous avons implémenté notre approche et mené une étude expérimentale sur des jeux de données réelles pour montrer l'intérêt de notre approche. L'approche GreC comprend différents algorithmes. Nous avons validé de manière expérimentale la pertinence de nos algorithmes et montrons leurs performances. / Online Analytical Processing (OLAP) is one of the most important technologies in data warehouse systems, which enables multidimensional analysis of data. It represents a very powerful and flexible analysis tool to manage within the data deeply by operating computation. OLAP has been the subject of improvements and extensions across the board with every new problem concerning domain and data; for instance, multimedia, spatial data, sequence data and etc. Basically, OLAP was introduced to analyze classical structured data. However, information networks are yet another interesting domain. Extracting knowledge inside large networks is a complex task and too big to be comprehensive. Therefore, OLAP analysis could be a good idea to look at a more compressed view. Many kinds of information networks can help users with various activities according to different domains. In this scenario, we further consider bibliographic networks formed on the bibliographic databases. This data allows analyzing not only the productions but also the collaborations between authors. There are research works and proposals that try to use OLAP technologies for information networks and it is called Graph OLAP. Many Graph OLAP techniques are based on a cube of graphs.In this thesis, we propose a new approach for Graph OLAP that is graphs enriched by cubes (GreC). In a different and complementary way, our proposal consists in enriching graphs with cubes. Indeed, the nodes or/and edges of the considered network are described by a cube. It allows interesting analyzes for the user who can navigate within a graph enriched by cubes according to different granularity levels, with dedicated operators. In addition, there are four main aspects in GreC. First, GreC takes into account the structure of network in order to do topological OLAP operations and not only classical or informational OLAP operations. Second, GreC has a global view of a network considered with multidimensional information. Third, the slowly changing dimension problem is taken into account in order to explore a network. Lastly, GreC allows data analysis for the evolution of a network because our approach allows observing the evolution through the time dimensions in the cubes.To evaluate GreC, we implemented our approach and performed an experimental study on a real bibliographic dataset to show the interest of our proposal. GreC approach includes different algorithms. Therefore, we also validated the relevance and the performances of our algorithms experimentally.

Nesta dissertação são feitas três abordagens. Na primeira apresentam-se os componentes necessários para que se possa compreender melhor o cenário atual onde se encontram aqueles que são os responsáveis pelo processo decisório nas empresas. São abordados as evoluções do processo decisório e do suporte ao mesmo, suas etapas e os seus fatores de influência. A segunda abordagem é relativa às três ferramentas que constituem a nova geração de Sistemas de Apoio à Decisão. A primeira ferramenta é o data warehouse, um banco de dados específico para propósitos gerenciais e que é independente dos bancos de dados operacionais. A segunda ferramenta é o On-Line Analytical Processing (OLAP) e é utilizada para se realizar análises sofisticadas, que permitem aos seus usuários compreenderem melhor os negócios que são realizados na empresa. A última ferramenta é o data mining que permite que se faça uma análise nos dados armazenados, durante anos, para que se descubram relacionamentos ocultos entres os dados, revelando perfis de compras e de clientes; desta forma, as informações obtidas podem se tornar estratégias de negócios. Com a abordagem destas três novas ferramentas, deseja-se analisar o que existe de mais avançado, atualmente, para dar um melhor suporte ao processo decisório, sem entrar nos detalhes estritamente técnicos destas tecnologias. A terceira abordagem é constituída de exemplos de empresas que implementaram estas ferramentas e os resultados obtidos, assim como pelas tendências destas ferramentas para os próximos anos. / In this dissertation we will deal with three approaches. On the first we present the necessary elements to make one understand better the current scenery where the responsible persons for the decision process of companies meet. The evolution of the decision process and its support, phases and influence factors. The second approach is related to the three tools that constitute the new generation of Decision Support Systems. The first tool is the data warehouse, a specific database for the managerial purposes that is independent from the operational databases. The second tool is the On-Line Analytical Processing (OLAP) used in carrying out sophisticated analyses allowing its users a better understanding of the business accomplished in the company. The last tool is the data mining that allows for an analysis of the data stored along the years so that one is able to find out the correct relationship among the collect’s data, revealing business and clients profiles. In such way all the information gathered in the process can be converted into business strategy. With the approach of these three new tools we intend to analyze the most advanced techniques available nowadays to give a better decision support without getting into strictly technical details of these technologies. The third approach is made up of examples of companies that implemented such tools and the attained results, as well, the trends for these tools in the coming years.

Este trabalho trata da especificação, desenvolvimento e utilização do Sistema de Apoio à Gestão de Utilidades e Energia - SAGUE, um sistema concebido para auxiliar na análise de dados coletados de sistemas de utilidades como ar comprimido, vapor, sistemas de bombeamento, sistemas para condicionamento ambiental e outros, integrados com medições de energia e variáveis climáticas. O SAGUE foi desenvolvido segundo conceitos presentes em sistemas de apoio à decisão como Data Warehouse e OLAP - Online Analytical Processing - com o intuito de transformar os dados oriundos de medições em informações que orientem diretamente as ações de conservação e uso racional de energia. As principais características destes sistemas, que influenciaram na especificação e desenvolvimento do SAGUE, são tratadas neste trabalho. Além disso, este texto aborda a gestão energética e os sistemas de gerenciamento de energia visando apresentar o ambiente que motivou o desenvolvimento do SAGUE. Neste contexto, é apresentado o Sistema de Gerenciamento de Energia Elétrica - SISGEN, um sistema de informação para suporte à gestão de energia elétrica e de contratos de fornecimento, cujos dados coletados podem ser analisados através do SAGUE. A aplicação do SAGUE é tratada na forma de um estudo de caso no qual se analisa a correlação existente entre o consumo de energia elétrica da CUASO - Cidade Universitária Armando de Sales Oliveira, obtido através do SISGEN, e as medições de temperatura ambiente, fornecidas pelo IAG - Instituto de Astronomia, Geofísica e Ciências Atmosféricas da USP. / This work deals with specification, development and utilization of the Support System for Utility and Energy Management - SAGUE, a system created to assist in analysis of data collected from utilities systems as compressed air, vapor, water pumping systems, environmental conditioning systems and others, integrated with energy consumption and climatic measurements. The development of SAGUE was based on concepts and methodologies from Decision Support System as Data Warehouse and OLAP - Online Analytical Processing - in order to transform data measurements in information that guide the actions for energy conservation and rational utilization. The main characteristics of Data Warehouse and OLAP tools that influenced in the specifications and development of SAGUE are described in this work. In addition, this text deals with power management and energy management systems in order to present the environment that motivated the SAGUE development. Within this context, it is presented the Electrical Energy Management System - SISGEN, a system for energy management support, whose electrical measurements can be analyzed by SAGUE. The SAGUE utilization is presented in a case study that discusses the relation between electrical energy consumption of CUASO - Cidade Universitária Armando de Sales Oliveira, obtained throughout SISGEN, and the local temperature measurements supplied by IAG - Institute of Astronomic and Atmospheric Science of USP.