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dc.contributor.authorIndelli Pisano, Valentina-
dc.date.accessioned2018-02-23T14:39:56Z-
dc.date.available2018-02-23T14:39:56Z-
dc.date.issued2017-04-20-
dc.identifier.urihttp://hdl.handle.net/10556/2617-
dc.identifier.urihttp://dx.doi.org/10.14273/unisa-1011-
dc.description2015 - 2016it_IT
dc.description.abstractData  warehouse  systems aim to support decision making by providing users with the appropriate  information  at  the right time. This task is particularly challenging in business contexts where large  amount of data is produced at a high speed. To this end, data warehouses have been equipped with  Online Analytical Processing tools that help users to make fast and precise decisions througt the  execution of complex queries. Since the computation of these queries is time consuming, data   warehouses precompute a set of materialized views answering to the workload  queries.   This thesis work defines a process to determine the minimal set of workload queries and the set of views to materialize. The set of queries is represented by an optimized lattice structure used to select  the views to be materialized according to the processing time costs and the view storage space. The minimal set of required Online Analytical Processing queries is computer by analyzing the data model defined with the visual language CoDe (Complexity Design). The latter allows to conceptually organizatio  the visualization of data reports and to generate visualizations of data obtained from data-­‐mart queries. CoDe adopts a hybrid modeling process combining two main methodologieser-­‐driven and data-­ driven. The first aims to create a model according to  the  user  knowledge,  re-quirements, and analysis needs, whilst the latter has in  charge to concretize data  and their relationships in the model through Online Analytical Processing queries. Since the materialized views change over time, we also propose a dynamic process that allows users to upgrade the CoDe model with a context-­‐aware editor, build an optimized lattice structure able to  minimize the effort to recalculate it,and propose the new set of views  to  materialize  Moreover,  the  process applies a Markov strategy to predict whether the views need to be recalculate or not  according to the changes of the model. The effectiveness of the proposed  techniques has  been  evaluated on a real world data warehouse. The results  revealed that the Markov strategy gives a better set of solutions in term of storage space and total processing cost. [edited by author]  it_IT
dc.language.isoenit_IT
dc.publisherUniversita degli studi di Salernoit_IT
dc.subjectViews selectionit_IT
dc.titleReducing the View Selection Problem through Code Modeling: Static and Dynamic approachesit_IT
dc.typeDoctoral Thesisit_IT
dc.subject.miurINF/01 INFORMATICAit_IT
dc.contributor.coordinatoreDe Lucia, Andreait_IT
dc.description.cicloXV n.sit_IT
dc.contributor.tutorG. Tortorait_IT
dc.identifier.Dipartimentodi Studi e Ricerche Aziendaliit_IT
Appears in Collections:Management and Information Technology

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Abstract in inglese V. Indelli Pisano.pdfabstract in inglese a cura dell'autore32,42 kBAdobe PDFView/Open


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