Towards a Big Data Reference Architecture Model for Swiss International Banks
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2017
Typ der Arbeit
Master
Studiengang
Sammlung
Typ
11 - Studentische Arbeit
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
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Verlag / Herausgebende Institution
Hochschule für Wirtschaft FHNW
Verlagsort / Veranstaltungsort
Olten
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
By now, many Swiss international banks see Big Data no more just as a buzzword, but as source of a new economic value and innovation. Big Data has gained in significance of how banking organizations are transforming themselves to deliver more value to customers, while cutting costs and mitigating credit, market and operational risks. Banks are now urged to expand their technical capabilities to allow them to work with and handle the sheer volume, variety and velocity of Big Data. New architectures must be considered for being able to cope with the explosive data growth and simultaneously being able to apply more complex algorithms in a flexible manner. The author of this master thesis enhances an existing, vendor-neutral, infrastructure- and technology-agnostic reference architecture model that was developed by the National Institute of Standards andTechnologies (NIST). The enhancements of the reference architecture model were done in strong collaboration with aSwiss international bank. Novel Big Data use cases were collected prior enhancing the model from NIST, with the intention to propose model enhancements that would harmonize with the selected use case (particularly based on their technical and business requirements). The aim of this research project is to suggest a generic Big Data reference architecture model that increases the transparency of the implementation of Big Data use cases.
Schlagwörter
Fachgebiet (DDC)
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Begutachtung
Open Access-Status
Lizenz
Zitation
Sykes, S. (2017). Towards a Big Data Reference Architecture Model for Swiss International Banks [Hochschule für Wirtschaft FHNW]. https://irf.fhnw.ch/handle/11654/39896