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Towards a Framework for Enterprise Architecture Analytics
Munich University of Applied Sciences.
Hochschule Aalen.
Hochschule Reutlingen.
University of Rostock.
Show others and affiliations
2014 (English)In: The 18th IEEE International EDOC Conference, Ulm, Germany, September 1-5, 2014, Ulm: IEEE Computer Society, 2014Conference paper, Published paper (Refereed)
Abstract [en]

Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. They are primarily model-driven and follow a top-down approach. Enterprise architecture uses semi-formal model created manually. In practice the resulting high effort often impedes the broad use of enterprise architecture methodologies. Furthermore, even if an architecture model is created in this way, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. Furthermore the compliance of Enterprise Architectures may be verified. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.

Place, publisher, year, edition, pages
Ulm: IEEE Computer Society, 2014.
Keyword [en]
Enterprise Analytics, Enterprise Architecture
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hj:diva-25478Scopus ID: 2-s2.0-84919773852OAI: oai:DiVA.org:hj-25478DiVA: diva2:775671
Conference
EDOC - IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations
Available from: 2015-01-04 Created: 2015-01-02 Last updated: 2015-06-09Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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