---
title: "Discussion on \"Validating Data Against Its Own History: Baseline Data Quality with GlueDQ\" | Hashnode"
description: "Discussion on \"Validating Data Against Its Own History: Baseline Data Quality with GlueDQ\". Row level checks catch nulls and bad types, but they wave through data that is well formed yet wrong, like a contributor whose arrears drop 90 percent in a month. The fix is a Hybrid Baseline check that validates each batch against its own"
url: "https://hashnode.com/posts/validating-data-against-its-own-history-baseline-data-quality-with-gluedq/6a53822612f045c55e25d084"
---

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# [Validating Data Against Its Own History: Baseline Data Quality with GlueDQ](https://sapotacorpvn.hashnode.dev/validating-data-against-its-own-history-baseline-data-quality-with-gluedq?utm_source=hashnode&utm_medium=feed)

Row level checks catch nulls and bad types, but they wave through data that is well formed yet wrong, like a contributor whose arrears drop 90 percent in a month. The fix is a Hybrid Baseline check that validates each batch against its own

Jul 12 · 8 min read · sapotacorpvn.hashnode.dev  
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-   [#data-engineering](https://hashnode.com/tag/data-engineering)
-   [#data-quality](https://hashnode.com/tag/data-quality)
-   [#aws-glue](https://hashnode.com/tag/aws-glue)
-   [#iceberg](https://hashnode.com/tag/iceberg)
-   [#lakehouse](https://hashnode.com/tag/lakehouse)

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@sapotacorpvn · Hanoi, Vietnam

  
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