A Prototyped NL-Based Approach for the Design of Multidimensional Data Warehouse

Abstract

Organizations are more and more interested in the Data Warehouse (DW) technology and data analytics to base their decision-making processes on scientific arguments instead of intuition. Despite the efforts invested, the DW design issue remains a great challenging research domain. The design quality of the DW depends on several aspects, as the requirement gathering. In this context, we propose a Natural Language (NL) based design approach, which is twofold, first, it facilitates the involvement of the decision-makers in the DW design process; indeed, NL can encourage the decision-makers to express their requirements as English-like sentences conform to NL-templates. Secondly, our approach aims to generate semi-automatically a DW schema from a set of requirements gathered as analytical queries compliant to the NL-templates. This design approach relies on (i) two easy-to-use NL-templates to specifying the analysis components, and (ii) a set of five heuristic rules for extracting the multidimensional concepts from the requirements. We demonstrate the feasibility of our approach by developing the prototype Natural Language Decisional Requirements to DW Schema (NLDR2DWS).