Title :
Scenario-driven architecture assessment methodology for large data analysis systems
Author :
Begoli, Edmon ; Chila, T.F. ; Inmon, W.H.
Author_Institution :
Comput. Sci. & Eng. Div., Oak Ridge Nat. Lab., Oak Ridge, TN, USA
Abstract :
The methodology we present in this paper emerged as a result of the technical and organizational assessment we conducted for a large data analytic system and for its expansion to support a significant new mission in healthcare domain. We developed a 4+1 dimensional approach for examining the different characteristics of a system with four traditional dimensions and a fifth, scenarios-based, dimension, introduced as an exploration device of the entire system in its business context. We present the principles, guidelines, and structure of the methodology as well as the results of the application of this process leading to a credible evaluation that better assesses current large data analysis systems than the previous, purely static assessment.
Keywords :
data analysis; health care; 4-1 dimensional approach; business context; data analysis systems; data analytic system; healthcare domain; scenario-driven architecture assessment methodology; Bismuth; Computer architecture; Data analysis; Data models; Data warehouses; Organizations; Architecture assessment; ETL; data analysis; data warehouse; databases; parallel systems;
Conference_Titel :
Systems Conference (SysCon), 2013 IEEE International
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-3107-4
DOI :
10.1109/SysCon.2013.6549857