By automating this process, the risk of human error is also eliminated. Diftong was shown to provide accurate results in test scenarios, bringing benefits to companies that need to validate the outputs of their workflows. Row-based and column-based statistics are used to quantify the results of the database comparison. This tool compares two tabular databases resulting from different versions of a workflow to detect and prevent potential unwanted alterations. We motivate the need for workflows and describe the implementation of a validation tool called Diftong. When organisations update and refine their data transformations to meet evolving requirements, it is imperative to ensure that the new version of a workflow still produces the correct output. Data validation is about verifying the correctness of data.
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