UPM Institutional Repository

Relational model vs. dimensional model-further experimentation on understandability of the two schemas


Mat Yusof, Sharmila and Sidi, Fatimah (2014) Relational model vs. dimensional model-further experimentation on understandability of the two schemas. In: Malaysian National Conference of Databases 2014 (MaNCoD 2014), 17 Sept. 2014, Universiti Putra Malaysia, Serdang, Selangor. (pp. 40-45). (Unpublished)


Data warehouse (DW) has been commonly accepted as a solution to support organization’s decision support. Despite technical aspects of DW implementation, one of the most important tasks that need to be considered is its data modeling. Data modeling is important as it deals with structuring the data so that users can easily access for decision support process. The two predominant data models in data warehouse project are dimensional model (i.e. Star Schema Diagram (SSD)) and relational model (i.e. Entity-Relationship Diagram (ERD)). The decision whether to build a data warehouse using either model has created controversy among practitioners. Semantic network theory support that SSD is better than ERD in terms of its understanding measures. However, previous studies have produced conflicting result regarding the support and claim. Thus, the objective of this study is to further explore whether one schema is better than another in terms of its understandability. This study aims to design and conduct an experiment that test the understandability of the SSD and ERD with schema complexity factor.

Download File

[img] PDF
Restricted to Repository staff only

Download (515kB)

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
Keywords: Data warehouse; Data modeling; Star schema diagram; Entity-relationship diagram; Data modeling; Understandability
Depositing User: Nursyafinaz Mohd Noh
Date Deposited: 18 Jun 2015 08:05
Last Modified: 29 Jul 2016 08:09
URI: http://psasir.upm.edu.my/id/eprint/38828
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item