Abstract
Extract-Transform-Load (ETL) workflows are data centric workflows responsible for transferring, cleaning, and loading data from their respective sources to the warehouse. In this paper, we build upon existing graph-based modeling techniques that treat ETL workflows as graphs by (a) extending the activity semantics to incorporate negation, aggregation and self-joins, (b) complementing querying semantics with insertions, deletions and updates, and (c) transforming the graph to allow zoom-in/out at multiple levels of abstraction (i.e., passing from the detailed description of the graph at the attribute level to more compact variants involving programs, relations and queries and vice-versa).
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Simitsis, A., Vassiliadis, P., Terrovitis, M., Skiadopoulos, S. (2005). Graph-Based Modeling of ETL Activities with Multi-level Transformations and Updates. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2005. Lecture Notes in Computer Science, vol 3589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546849_5
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DOI: https://doi.org/10.1007/11546849_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28558-8
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