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Incremental consolidation of data-intensive multi-flows
Jovanovic, Petar; Romero Moral, Óscar; Simitsis, Alkis; Abelló Gamazo, Alberto
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació; Universitat Politècnica de Catalunya. MPI - Modelització i Processament de la Informació
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Business intelligence (BI) systems depend on efficient integration of disparate and often heterogeneous data. The integration of data is governed by data-intensive flows and is driven by a set of information requirements. Designing such flows is in general a complex process, which due to the complexity of business environments is hard to be done manually. In this paper, we deal with the challenge of efficient design and maintenance of data-intensive flows and propose an incremental approach, namely CoAl, for semi-automatically consolidating data-intensive flows satisfying a given set of information requirements. CoAl works at the logical level and consolidates data flows from either high-level information requirements or platform-specific programs. As CoAl integrates a new data flow, it opts for maximal reuse of existing flows and applies a customizable cost model tuned for minimizing the overall cost of a unified solution. We demonstrate the efficiency and effectiveness of our approach through an experimental evaluation using our implemented prototype.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Enginyeria del software
Business intelligence--Data processing
Storage area networks (Computer networks)
Workflow--Management--Computer programs
Business Intelligence
data warehousing
data-intensive flows
workflow management
Espionatge industrial -- Programes d'ordinador
Xarxes d'emmagatzematge (Xarxes d'ordinadors)
Cicle de treball -- Programari
info:eu-repo/semantics/submittedVersion
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