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

    9 Citations (Scopus)

    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 Computer Society
    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 Sep 20145 Sep 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
    CountryGermany
    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

    Cite this

    Veneberg, R. K. M., Iacob, M. E., van Sinderen, M. J., & Bodenstaff, L. (2014). Enterprise architecture intelligence. In M. U. Reichert, S. Rinderle-Ma, & G. Grossmann (Eds.), Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014 (pp. 22-31). USA: IEEE Computer Society. https://doi.org/10.1109/EDOC.2014.14
    Veneberg, R.K.M. ; Iacob, Maria Eugenia ; van Sinderen, Marten J. ; Bodenstaff, L. / Enterprise architecture intelligence. Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014. editor / M.U. Reichert ; S. Rinderle-Ma ; G. Grossmann. USA : IEEE Computer Society, 2014. pp. 22-31
    @inproceedings{e6bd7e12b6b34537af5cff1b7b40f275,
    title = "Enterprise architecture intelligence",
    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.",
    keywords = "Operational data, SCS-Services, EWI-25047, Data warehouse, Quantitative analysis, Business intelligence, IR-91750, METIS-306021, Enterprise Architecture",
    author = "R.K.M. Veneberg and Iacob, {Maria Eugenia} and {van Sinderen}, {Marten J.} and L. Bodenstaff",
    note = "10.1109/EDOC.2014.14",
    year = "2014",
    doi = "10.1109/EDOC.2014.14",
    language = "Undefined",
    isbn = "978-1-4799-5470-4",
    publisher = "IEEE Computer Society",
    pages = "22--31",
    editor = "M.U. Reichert and S. Rinderle-Ma and G. Grossmann",
    booktitle = "Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014",
    address = "United States",

    }

    Veneberg, RKM, Iacob, ME, van Sinderen, MJ & Bodenstaff, L 2014, Enterprise architecture intelligence. in MU Reichert, S Rinderle-Ma & G Grossmann (eds), Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014. IEEE Computer Society, USA, pp. 22-31, 18th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014, Ulm, Germany, 3/09/14. https://doi.org/10.1109/EDOC.2014.14

    Enterprise architecture intelligence. / Veneberg, R.K.M.; Iacob, Maria Eugenia; van Sinderen, Marten J.; Bodenstaff, L.

    Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014. ed. / M.U. Reichert; S. Rinderle-Ma; G. Grossmann. USA : IEEE Computer Society, 2014. p. 22-31.

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

    TY - GEN

    T1 - Enterprise architecture intelligence

    AU - Veneberg, R.K.M.

    AU - Iacob, Maria Eugenia

    AU - van Sinderen, Marten J.

    AU - Bodenstaff, L.

    N1 - 10.1109/EDOC.2014.14

    PY - 2014

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    N2 - 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.

    AB - 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.

    KW - Operational data

    KW - SCS-Services

    KW - EWI-25047

    KW - Data warehouse

    KW - Quantitative analysis

    KW - Business intelligence

    KW - IR-91750

    KW - METIS-306021

    KW - Enterprise Architecture

    U2 - 10.1109/EDOC.2014.14

    DO - 10.1109/EDOC.2014.14

    M3 - Conference contribution

    SN - 978-1-4799-5470-4

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    BT - Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014

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    A2 - Rinderle-Ma, S.

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    Veneberg RKM, Iacob ME, van Sinderen MJ, Bodenstaff L. Enterprise architecture intelligence. In Reichert MU, Rinderle-Ma S, Grossmann G, editors, Eighteenth IEEE International Enterprise Distributed Object Computing Conference, EDOC 2014. USA: IEEE Computer Society. 2014. p. 22-31 https://doi.org/10.1109/EDOC.2014.14