Abstract
Multidimensional schemas are used to model data warehouse systems, a special type of large databases dedicated for decision support. Several approaches have been proposed in this domain to ensure the satisfaction of decision makers needs and the accuracy of the generated schemas. This paper presents an approach for the validation of multidimensional star schema assisted by repair solutions. Our approach aims to assist designers by detecting constraint violations and proposing repair solutions based on a number of error-based rules formalized in Prolog. Its efficiency stems from using both linguistic similarity computation and a set of heuristics developed by bottom-up design methods to produce warnings about semantic constraint violations and their impact on the quality of the analysis results.
Highlights
Face to the international, unrestrained economic competition, an increasing interest in decision support systems has emerged over the last two decades
The quality of a multidimensional schema was extensively addressed in the literature on data warehousing, through metrics defined in terms of the structural elements of the schemas and through sets of constraints defined at the model level
We proposed an approach for the design of valid multidimensional schemas
Summary
Face to the international, unrestrained economic competition, an increasing interest in decision support systems has emerged over the last two decades. Similar to any software system, the efficient development of a decision support system depends on the quality of its models (specification and design, in particular) In their attempts to model a decision support system based on the data warehouse approach, the proposed methods have often relied on various multidimensional models to specify data mart schemas, including the star, constellation, and snowflake schema models [20,25]. It complements existing design approaches by offering a framework for the analysis of the structural, conformity and semantic constraints satisfaction of the schemas they produce It aims at assisting designers by detecting constraint violations and proposing repair solutions based on a number of rules formalized in Prolog.
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