Utilizing Semantic Web Technologies for Efficient Data Lineage and Impact Analyses in Data Warehouse Environments

Data warehouse (DWH) systems play an important role in the IT landscapes of today's enterprises. In order to cope with the complex transformation processes and big data volumes, they have to be supplemented by metadata. Two main uses of such metadata are data lineage analyses, allowing data elements within the DWH to be traced back to their origin, and impact analyses, revealing which other elements may be impacted by planned modifications to certain data elements. As these types of queries operate on graphs (data elements being transformed through the different DWH layers), Semantic Web technologies should provide a perfect toolset. However, today's metadata management tools utilize proprietary or regular SQL storage and querying mechanisms. Hence, this paper reviews the applicability of Semantic Web technologies for performing efficient data lineage or impact analyses in. DWH environments.