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* DOCS - Prepare 1.7 Release and 1.8 SNAPSHOT * DOCS - Prepare 1.7 Release and 1.8 SNAPSHOT
24 lines
1.6 KiB
Markdown
24 lines
1.6 KiB
Markdown
---
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title: Data Quality Overview Section
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slug: /how-to-guides/data-quality-observability/quality/overview
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collate: true
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---
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# Data Quality Overview Section
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The SaaS version of Collate offers an overview of the data quality test results grouped by dimensions. This gives users a quick insight about data quality performance centered around meaningful categories.
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The 6 categories are defined as:
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- **Completeness**: contains test cases allowing user to validate if any values are missing from a column/table (e.g. Column Values To Be Not Null)
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- **Accuracy**: contains test cases allowing user to validate if any values represent their expected values in the real world (e.g. Column Value Max To Be Between)
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- **Consistency**: contains test cases allowing user to validate the information stored between data processing is consistent with the expectations (e.g. Table Data Diff)
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- **Validity**: contains test cases allowing user to control the data represent the specifications/expectations of the domain (e.g. Column Values To Not Match Regex)
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- **Uniqueness**: contains test cases allowing user to control for potential duplicates in the data (e.g. Column Values To Be Unique)
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- **Integrity**: contains test cases allowing user to validate the integrity of entity attributes (e.g. Table Column Count To Be Between)
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For a full list of test cases and their dimensions click [here](/how-to-guides/data-quality-observability/quality/tests-yaml)
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{% image
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src="/images/v1.7/features/ingestion/workflows/data-quality/data-quality-dimensions.png"
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alt="Data Quality Overview"
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caption="Data Quality Overview"
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/%} |