Saturday, December 4, 2021
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The importance of validation in data ingest

When constructing your data ingest pipeline, the exciting stuff is the transformation – the mappings, reformattings and changes you build into your processes. But how much time are you spending fixing problems with data after it’s been through that transformation stage? Are you accounting not just for format requirements but for inefficiencies that occur when the data isn’t fully validated, either immediately fixing the problem or down the line when an error or missing data set is discovered?

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