Data Warehouse as a Backbone for Business Intelligence: Issues and Challenges

Abstract

The aim of this research is to identify and classify the main issues and challenges facing different business organizations when implementing Data Warehouse (DW) technologies. This is highly significant given the theoretical and practical implications and importance of such technologies. It is also important to highlight these challenges given the scarcity of research in this domain despite its value. To determine DW issues and challenges, a qualitative research methodology was followed. A semi-structured interview protocol was used with 17 DW project managers and seniors’ members. The gathered data were analyzed by utilizing a bottom-up content analysis technique where content is coded and classified thematically so as to let concepts emerge naturally. The study results show that DW issues and challenges are both managerial/organizational and technological. According to the results of the study, the main managerial/organizational DW challenges are: (1) management commitment and support; (2) project champion; (3) user involvement and participation; and (4) team skills and composition, whereas the technological challenges are: (1) the selection of DW architecture; (2) the creation of the enterprise schema; (3) data integration and scalability; (4) data quality; (5) the design of human-computer interfaces; (6) mining the DW; (7) security and privacy risks; and (8) networks and telecommunications.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.