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Integration and analysis of data from different sources have to deal with several problems resulting from potential heterogeneities. The activities addressing these problems are called data preparation and are supported by various available tools. However, these tools process mostly in a batch-like manner, not supporting the iterative and explorative nature of the integration and analysis process. The authors present a framework for important data preparation tasks based on a multidatabase language. This language offers features for solving common integration and cleaning problems as part of query processing. Combining data preparation mechanisms and multidatabase query facilities permits applying and evaluating different integration and cleaning strategies without explicit loading and materialization of data. The paper introduces the language concepts and discusses their application for individual tasks of …