Start Date
16-8-2018 12:00 AM
Description
The big data digital trend revolutionizes how enterprises conduct their business. Big data transforms how business models are created, services and products are provided, processes are optimized and IT landscapes are designed. Today, enterprise architecture (EA) models are used in many organizations to capture the complex interplay between business, organizational and IT elements in order to support strategy development, transformation and project management. Based on a literature review on big data challenges, this paper outlines necessary extensions for EA models. Following an incremental research approach, exemplary stakeholder concerns and relevant modeling elements are derived from (1) data, (2) process and (3) management challenges. On this basis, an extended EA meta-model for big data is developed.
Recommended Citation
Burmeister, Fabian; Drews, Paul; and Schirmer, Ingrid, "Towards an Extended Enterprise Architecture Meta-Model for Big Data - A Literature-based Approach" (2018). AMCIS 2018 Proceedings. 2.
https://aisel.aisnet.org/amcis2018/Enterprise/Presentations/2
Towards an Extended Enterprise Architecture Meta-Model for Big Data - A Literature-based Approach
The big data digital trend revolutionizes how enterprises conduct their business. Big data transforms how business models are created, services and products are provided, processes are optimized and IT landscapes are designed. Today, enterprise architecture (EA) models are used in many organizations to capture the complex interplay between business, organizational and IT elements in order to support strategy development, transformation and project management. Based on a literature review on big data challenges, this paper outlines necessary extensions for EA models. Following an incremental research approach, exemplary stakeholder concerns and relevant modeling elements are derived from (1) data, (2) process and (3) management challenges. On this basis, an extended EA meta-model for big data is developed.