TU Berlin

Big Data Management GroupData Transformation Discovery


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Data Transformation Discovery


Data transformation is a crucial step in data integration. While some transformations, such as liters to gallons, can be easily performed by applying a formula or a program on the input values, others, such as zip code to city, require sifting through a repository containing explicit value mappings. There are already powerful systems that provide formulae and algorithms for transformations. However, the automated identication of reference datasets to support value mapping remains largely unresolved. The Web is home to millions of tables with many containing explicit value mappings. This is in addition to value mappings hidden behind Web forms. In this work, we presented DataXFormer, a transformation engine that leverages Web tables and Web forms to perform transformation tasks. The project results were published at CIDR 2015, SIGMOD 2015, and ICDE 2016.

The Demonstration at SIGMOD 2015 won the Best Demonstration Award.


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