Active XML Data Warehouses for Intelligent, On-line Decision Support PDF Download

Author: Rashed Salem
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Languages : en
Pages : 0

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Book Description
A decision support system (DSS) is an information system that supports decisionmakers involved in complex decision-making processes. Modern DSSs needto exploit data that are not only numerical or symbolic, but also heterogeneouslystructured (e.g., text and multimedia data) and coming from various sources (e.g,the Web). We term such data complex data. Data warehouses are casually usedas the basis of such DSSs. They help integrate data from a variety of sourcesto support decision-making. However, the advent of complex data imposes anothervision of data warehousing including data integration, data storage and dataanalysis. Moreover, today's requirements impose integrating complex data in nearreal-time rather than with traditional snapshot and batch ETL (Extraction, Transformationand Loading). Real-time and near real-time processing requires a moreactive ETL process. Data integration tasks must react in an intelligent, i.e., activeand autonomous way, to encountered changes in the data integration environment,especially data sources.In this dissertation, we propose novel solutions for complex data integration innear real-time, actively and autonomously. We indeed provide a generic metadatabased,service-oriented and event-driven approach for integrating complex data.To address data complexity issues, our approach stores heterogeneous data into aunied format using a metadata-based approach and XML. We also tackle datadistribution and interoperability using a service-oriented approach. Moreover, toaddress near real-time requirements, our approach stores not only integrated datainto a unied repository, but also functions to integrate data on-the-y. We also apply a service-oriented approach to track relevant data changes in near real-time.Furthermore, the idea of integrating complex data actively and autonomously revolvesaround mining logged events of data integration environment. For this sake,we propose an incremental XML-based algorithm for mining association rules fromlogged events. Then, we de ne active rules upon mined data to reactivate integrationtasks.To validate our approach for managing complex data integration, we develop ahigh-level software framework, namely AX-InCoDa (Active XML-based frameworkfor Integrating Complex Data). AX-InCoDa is implemented as Web application usingopen-source tools. It exploits Web standards (e.g., XML and Web services) andActive XML to handle complexity issues and near real-time requirements. Besidewarehousing logged events into an event repository to be mined for self-managingpurposes, AX-InCoDa is enriched with active rules. AX-InCoDa's feasibility is illustratedby a healthcare case study. Finally, the performance of our incremental eventmining algorithm is experimentally demonstrated.