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Data-intensive software programs typically transform a set of source data values into target data values. While the group of developers who write, compile and test the software or the query have a clear understanding of the transformation logic (or transformation rules) at the time the program is created, that understanding can quickly fade at an enterprise level for a variety of reasons, inclu...

Program analysis for typings, for set inclusion and membership relationships, and for universal sets to support data structure selection was a major goal of the SETL project and involved perhaps 50 person-years of design and implementation. Because that approach was so comprehensive, its data structure algorithms used heuristics leading only to expected improvements in performance. Despite seri...

A two-level data transformation consists of a type-level transformation of a data format coupled with value-level transformations of data instances corresponding to that format. Examples of two-level data transformations include XML schema evolution coupled with document migration, and data mappings used for interoperability and persistence. We provide a formal treatment of two-level data trans...

This paper discusses data quality challenges in the context of eBusiness Transformation. It presents the major differences between traditional and eBusiness as they relate to business models, organizations, processes and technologies, and then outlines the differences with respect to data quality approaches. The scenarios described pose significant data quality (and other) challenges, and the p...

This paper addresses DW design problems, with the goal of improving the DW logical design process. Some of the existing work in transformation oriented methodologies for DW design construct the DW starting from an EntityRelationship model of the source database, and arrive to a conceptual or highlevel-logical dimensional model of the DW. We propose a mechanism for obtaining the DW logical schem...