> ## Documentation Index > Fetch the complete documentation index at: https://docs.getcollate.io/llms.txt > Use this file to discover all available pages before exploring further. # Data Quality Overview Section # Data Quality Overview Section 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. The 6 categories are defined as: * **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) * **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) * **Consistency**: contains test cases allowing user to validate the information stored between data processing is consistent with the expectations (e.g. Table Data Diff) * **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) * **Uniqueness**: contains test cases allowing user to control for potential duplicates in the data (e.g. Column Values To Be Unique) * **Integrity**: contains test cases allowing user to validate the integrity of entity attributes (e.g. Table Column Count To Be Between) For a full list of test cases and their dimensions click [here](/how-to-guides/data-quality-observability/quality/tests-yaml) Data Quality Overview