TITLE:
Knowledge Discovery in Data: A Case Study
AUTHORS:
Ahmed Hammad, Simaan AbouRizk
KEYWORDS:
Construction Management; Project Management; Knowledge Management; Data Warehousing; Data Mining; Knowledge Discovery in Data (KDD); Industrial Construction; Labour Resources
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.5,
March
10,
2014
ABSTRACT:
It is common in industrial construction projects for data to be
collected and discarded without being analyzed to extract useful knowledge. A
proposed integrated methodology based on a five-step Knowledge Discovery in
Data (KDD) model was developed to address this issue. The framework transfers
existing multidimensional historical data from completed projects into useful
knowledge for future projects. The model starts by understanding the problem
domain, industrial construction projects. The second step is analyzing the
problem data and its multiple dimensions. The target dataset is the labour
resources data generated while managing industrial construction projects. The
next step is developing the data collection model and prototype data ware-house. The data warehouse
stores collected data in a ready-for-mining format and produces dynamic On Line
Analytical Processing (OLAP) reports and graphs. Data was collected from a
large western-Canadian structural steel fabricator to prove the applicability
of the developed methodology. The proposed framework was applied to three
different case studies to validate the applicability of the developed framework
to real projects data.