Towards a Matrix Based Approach for Analyzing the Impact of Change on ETL Processes
Extraction, Transformation and Loading (ETL) processes aim to
extract data from data sources to targets, via a set of
transformations. In many situations, an ETL process can be
subject to changes for several reasons. For instance, data sources
changes, new requirements and bug fixing. When changes
happen, analyzing the impact of change is mandatory to avoid
errors and mitigate the risk of breaking existent treatments.
Several solutions have been proposed for this issue. We propose
a new approach, based on matrices, for analyzing the impact of
change on ETL processes. The goal of this paper is to present the
theoretical fundament of our approach. We model ETL parts as
matrices then we propose an algorithm which detects the affected
parts in an ETL process, given an attribute deletion event.
Compared with the existent solutions, our approach has the
advantage of easiness.
Keywords: Data warehouse, ETL processes, Conceptual modeling of ETL processes, Impact of Change
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