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The Power of a Model-Driven Approach to Handle Evolving Data Warehouse Requirements

机译:用于处理演化数据仓库要求的模型驱动方法的力量

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The Data Warehouse (DW) is characterized by complex architecture, specific modeling and design approaches. It integrates data issued from operational data sources in order to meet decision-makers' needs by providing answers for OLAP queries (On-Line Analytical Processing). In practice, both data source models and decision-makers' analytical requirements evolve over time and, therefore, lead to changes in the DW multidimensional model. In this evolving context, we have developed the DWE (Data Warehouse Evolution) framework. DWE automatically propagates the changes of the data source data-model on the DW data-model. This paper proposes a model-driven approach for extending DWE in order to consider a further related evolutionary aspect: The evolution of decision-makers' needs. It deals with the propagation of these evolutions on the DW multidimensional model. This approach relies on a classification of evolution scenarios and a set of transformation rules for the identification of evolution operations to apply on the DW.
机译:数据仓库(DW)的特点是复杂的架构,特定建模和设计方法。它集成了从运营数据源发出的数据,以便通过为OLAP查询提供答案(在线分析处理)来满足决策者的需求。在实践中,数据源模型和决策者的分析要求随着时间的推移而发展,因此导致DW多维模型的变化。在这种不断发展的背景下,我们开发了DWE(数据仓库演进)框架。 DWE自动传播DW数据模型上的数据源数据模型的更改。本文提出了一种用于延伸DWE的模型驱动方法,以便考虑进一步相关的进化方面:决策者需求的演变。它涉及这些演变对DW多维模型的传播。这种方法依赖于演进方案的分类和一组转换规则,用于识别在DW上应用进化操作。

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