Framing Semantic Data Warehousing from a Systems Perspective

Abstract

The challenge associated with data warehousing has escalated in the era of big data with masses of fast-moving heterogeneous data sources. As organisations attempt to exploit an ever-growing complex and dynamic datasphere, traditional data warehousing practices seem to produce systems that are inflexible and unable to scale. In a dynamic world of flux and change, systemic process thinking provides an alternative paradigm from which to approach the data warehousing challenge. This paper provides a framing of semantic data warehousing from such a systems perspective. Semantic data warehousing involves data semantification – enriching data with its context and meaning – to achieve higher levels of automation and adaptability. The framing elucidates the inherent systems approach of incorporating semantic technologies and automated dimensionalisation in data warehousing. It provides a case for the data management community to appreciate and accept complexity and multiple perspectives, and to incorporate systemic process thinking and semantic relativism into data management practices.