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Article
Current trends and future directions in the practice of high-level data modeling: An empirical study
ECIS 2009 Proceedings
  • BARBARA ANGLIM, Monash University
  • SIMON MILTON, The University of Melbourne
  • JAYANTHA RAJAPAKSE, Monash University
  • RON WEBER, Monash University
Publication Date
1-1-2009
Abstract

Many organizations now purchase and customize software rather than build information systems. In this light, some argue that high-level data modeling no longer has a role. In this paper, we examine the contemporary relevance of high-level data modeling. We addressed this issue by asking 21 experienced data-modeling practitioners to reflect on their work and to give their opinions on trends and future directions in high-level data modeling. We analyzed transcripts of our interviews with them using Klein and Myers’s (1999) framework for qualitative research. We found considerable variation in the practice of high-level data modeling. We also found that high-level data modeling is still considered important, even though organizations ultimately may purchase off-the-shelf software. The reason is that high-level data modeling assists organizations to obtain clarity about IT project scope and requirements, thereby reducing the risk that costly implementation mistakes will be made.

Citation Information
BARBARA ANGLIM, SIMON MILTON, JAYANTHA RAJAPAKSE and RON WEBER. "Current trends and future directions in the practice of high-level data modeling: An empirical study" (2009)
Available at: http://works.bepress.com/ron_weber/4/