919 resultados para ON-LINE ANALYTICAL PROCESSING (OLAP)
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Operatiivisen tiedon tuottaminen loppukäyttäjille analyyttistä tarkastelua silmällä pitäen aiheuttaa ongelmia useille yrityksille. Diplomityö pyrkii ratkaisemaan ko. ongelman Teleste Oyj:ssä. Työ on jaettu kolmeen pääkappaleeseen. Kappale 2 selkiyttää On-Line Analytical Processing (OLAP)- käsitteen. Kappale 3 esittelee muutamia OLAP-tuotteiden valmistajia ja heidän arkkitehtuurejaan sekä tyypillisten sovellusalueiden lisäksi huomioon otettavia asioita OLAP käyttöönoton yhteydessä. Kappale 4, tuo esille varsinaisen ratkaisun. Teknisellä arkkitehtuurilla on merkittävä asema ratkaisun rakenteen kannalta. Tässä on sovellettu Microsoft:n tietovarasto kehysrakennetta. Kappaleen 4 edetessä, tapahtumakäsittelytieto muutetaan informaatioksi ja edelleen loppukäyttäjien tiedoksi. Loppukäyttäjät varustetaan tehokkaalla ja tosiaikaisella analysointityökalulla moniulotteisessa ympäristössä. Vaikka kiertonopeus otetaan työssä sovellusesimerkiksi, työ ei pyri löytämään optimaalista tasoa Telesten varastoille. Siitä huolimatta eräitä parannusehdotuksia mainitaan.
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A conceptual information system consists of a database together with conceptual hierarchies. The management system TOSCANA visualizes arbitrary combinations of conceptual hierarchies by nested line diagrams and allows an on-line interaction with a database to analyze data conceptually. The paper describes the conception of conceptual information systems and discusses the use of their visualization techniques for on-line analytical processing (OLAP).
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About ten years ago, triadic contexts were presented by Lehmann and Wille as an extension of Formal Concept Analysis. However, they have rarely been used up to now, which may be due to the rather complex structure of the resulting diagrams. In this paper, we go one step back and discuss how traditional line diagrams of standard (dyadic) concept lattices can be used for exploring and navigating triadic data. Our approach is inspired by the slice & dice paradigm of On-Line-Analytical Processing (OLAP). We recall the basic ideas of OLAP, and show how they may be transferred to triadic contexts. For modeling the navigation patterns a user might follow, we use the formalisms of finite state machines. In order to present the benefits of our model, we show how it can be used for navigating the IT Baseline Protection Manual of the German Federal Office for Information Security.
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Current commercial and academic OLAP tools do not process XML data that contains XLink. Aiming at overcoming this issue, this paper proposes an analytical system composed by LMDQL, an analytical query language. Also, the XLDM metamodel is given to model cubes of XML documents with XLink and to deal with syntactic, semantic and structural heterogeneities commonly found in XML documents. As current W3C query languages for navigating in XML documents do not support XLink, XLPath is discussed in this article to provide features for the LMDQL query processing. A prototype system enabling the analytical processing of XML documents that use XLink is also detailed. This prototype includes a driver, named sql2xquery, which performs the mapping of SQL queries into XQuery. To validate the proposed system, a case study and its performance evaluation are presented to analyze the impact of analytical processing over XML/XLink documents.
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The concepts of on-line transactional processing (OLTP) and on-line analytical processing (OLAP) are often confused with the technologies or models that are used to design transactional and analytics based information systems. This in some way has contributed to existence of gaps between the semantics in information captured during transactional processing and information stored for analytical use. In this paper, we propose the use of a unified semantics design model, as a solution to help bridge the semantic gaps between data captured by OLTP systems and the information provided by OLAP systems. The central focus of this design approach is on enabling business intelligence using not just data, but data with context.
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Tese submetida à Universidade Portucalense para obtenção do grau de Mestre em Informática, elaborada sob a orientação de Prof. Doutor Reis Lima e Eng. Jorge S. Coelho.
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Dissertação de Mestrado
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Se basa en un análisis teórico de los sistemas de información como lo es el almacenaje de datos, cubos OLAP e inteligencia de negocios. Seguidamente, se hace un análisis de los sectores económicos de Colombia con un especial interés sobre el sector de alimentos, de esta manera conceptualizar la empresa sobre la cual este trabajo se enfocara. Se encontrará un análisis del caso de éxito Summerwood Corporation, el cual brindará una justificación para la propuesta final presentada a la empresa Dipsa Food, Pyme dedicada a la producción de alimentos no perecederos ubicada en la ciudad de Bogotá D.C –Colombia, la cual tiene gran interés en cuanto al desarrollo de nuevas tecnologías que brinden información fidedigna para la toma de decisiones
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Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.
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The increasing availability of mobility data and the awareness of its importance and value have been motivating many researchers to the development of models and tools for analyzing movement data. This paper presents a brief survey of significant research works about modeling, processing and visualization of data about moving objects. We identified some key research fields that will provide better features for online analysis of movement data. As result of the literature review, we suggest a generic multi-layer architecture for the development of an online analysis processing software tool, which will be used for the definition of the future work of our team.
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Diplomityön tavoitteena oli selvittää erilaisia jatkojalostusmahdollisuuksia, joilla voidaan nostaa suuren mäntysahan tuotteiston arvoa. Lisäksi tuli tarkastella jalostuksen integrointia sahan tuotantoprosessiin. Työn taustalla on toisaalta puutuotemarkkinoiden muuttuminen ja toisaalta raaka-aineen laadullinen huononeminen. Molemmat seikat vaikuttavat negatiivisesti perinteisen mäntysahan kannattavuuteen .Jatkojalostuksen integroinnilla sahatavaraprosessiin saavutetaan säästöjä tuotantokustannuksissa, kun tarkastellaan koko prosessia tukista jatkojalosteeksi. Myös raaka-aineen tuottavuutta voidaan nostaa integraation avulla. Jatkojalostus voidaan integroida sahatavaraprosessiin raaka-aineen valikoinnilla sahatavaraprosessin eri osissa, on-line –jalostuksella sekä taloudellisesti. Sahatavaraprosessissa tapahtuva raaka-aineen valikointi voidaan suorittaa tukeista ja sahatavarasta. Valikointikriteerinä voi olla puun ominaisuudet, sahatavaran mitat ja laatu. Valikointiin voidaan nykyteknologiasta hyödyntää röntgentekniikkaa sekä konenäköä. On-line –jalostus tarkoittaa kiinteästi sahatavaraprosessiin liittyvää jalostusta, jolloin ns. turhia prosessivaiheita jää pois ja syntyy säästöjä. On-line –jalostuksen edellytys on raaka-aineen jonkin asteinen valikointi, esim. pituus. Taloudellisesti integroitu jalostus tarkoittaa, että jalostuslaitoksella pyritään nollatulokseen ja jalostuksen lisäarvo palautetaan sahan toimittamaan raaka-aineen hintaan. Tällainen toiminta yhtiön sisällä poistaa turhaa keskustelua raaka-aineen siirtohinnoista ja siten vapauttaa osaltaan resursseja tuottavampaan toimintaan. Erilaisten jatkojalostusmuotojen ja puun ominaisuuksien hyödyntämisen seulonnan perusteella löytyi yksi jalostusmuoto, jolla voidaan kohottaa mäntysahan tuotteiston arvoa. Työn tuloksena syntyi investointiehdotus aihiotankotuotannosta ikkunateollisuuden tarpeisiin. Raaka-aineen hyödynnettäviä ominaisuuksia ovat männyn sydänpuun luonnollinen kestävyys sekä keskimääräinen oksaväli. Valikointi tehdään välitukeista, joiden sahaamisen kannattavuus on männyn rungon osista heikoin. Aihiotankoprosessissa hyödynnetään konenäköä ja sormijatkostekniikkaa. Jatkojalostuksen integrointi sahatavaraprosessiin toteutetaan rakentamalla on-line –jalostuslaitos sekä soveltamalla röntgentekniikkaa raaka-aineen valinnassa.
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In database marketing, the behavior of customers is analyzed by studying the transactions they have performed. In order to get a global picture of the behavior of a customer, his single transactions have to be composed together. In On-Line Analytical Processing, this operation is known as reverse pivoting. With the ongoing data analysis process, reverse pivoting has to be repeated several times, usually requiring an implementation in SQL. In this paper, we present a construction for conceptual scales for reverse pivoting in Conceptual Information Systems, and also discuss the visualization. The construction allows the reuse of previously created queries without reprogramming and offers a visualization of the results by line diagrams.
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Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.
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In the last few years, a new generation of Business Intelligence (BI) tools called BI 2.0 has emerged to meet the new and ambitious requirements of business users. BI 2.0 not only introduces brand new topics, but in some cases it re-examines past challenges according to new perspectives depending on the market changes and needs. In this context, the term pervasive BI has gained increasing interest as an innovative and forward-looking perspective. This thesis investigates three different aspects of pervasive BI: personalization, timeliness, and integration. Personalization refers to the capacity of BI tools to customize the query result according to the user who takes advantage of it, facilitating the fruition of BI information by different type of users (e.g., front-line employees, suppliers, customers, or business partners). In this direction, the thesis proposes a model for On-Line Analytical Process (OLAP) query personalization to reduce the query result to the most relevant information for the specific user. Timeliness refers to the timely provision of business information for decision-making. In this direction, this thesis defines a new Data Warehuose (DW) methodology, Four-Wheel-Drive (4WD), that combines traditional development approaches with agile methods; the aim is to accelerate the project development and reduce the software costs, so as to decrease the number of DW project failures and favour the BI tool penetration even in small and medium companies. Integration refers to the ability of BI tools to allow users to access information anywhere it can be found, by using the device they prefer. To this end, this thesis proposes Business Intelligence Network (BIN), a peer-to-peer data warehousing architecture, where a user can formulate an OLAP query on its own system and retrieve relevant information from both its local system and the DWs of the net, preserving its autonomy and independency.