Enterprise architecture intelligence

R.K.M. Veneberg, Maria Eugenia Iacob, Marten J. van Sinderen, L. Bodenstaff

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    16 Citations (Scopus)
    14 Downloads (Pure)

    Abstract

    Combining enterprise architecture and operational data is complex (especially when considering the actual ‘matching’ of data with enterprise architecture objects), and little has been written on how to do this. Therefore, in this paper we aim to fill this gap and propose a method to combine operational data with enterprise architecture to better support decision-making. Using such a method may result either in an enriched enterprise architecture model (which is very suitable as basis for model-based architecture analyses), or in a warehouse data model where operational data is enriched with enterprise architecture metadata (which leads to more traceability by easing the retrieval and interpretation of raw data, and of business analytics results). The method is illustrated by means of a case study. Also, a model to store enterprise architecture, operational data and time is presented on which new forms of analysis may be performed.
    Original languageUndefined
    Title of host publicationEighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014
    EditorsM.U. Reichert, S. Rinderle-Ma, G. Grossmann
    Place of PublicationUSA
    PublisherIEEE
    Pages22-31
    Number of pages10
    ISBN (Print)978-1-4799-5470-4
    DOIs
    Publication statusPublished - 2014
    Event18th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014 - Ulm, Germany
    Duration: 3 Sept 20145 Sept 2014
    Conference number: 18

    Publication series

    Name
    PublisherIEEE Computer Society
    ISSN (Print)1541-7719

    Conference

    Conference18th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014
    Abbreviated titleEDOC
    Country/TerritoryGermany
    CityUlm
    Period3/09/145/09/14

    Keywords

    • Operational data
    • SCS-Services
    • EWI-25047
    • Data warehouse
    • Quantitative analysis
    • Business intelligence
    • IR-91750
    • METIS-306021
    • Enterprise Architecture

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