# Measure

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Reliable data serves as the bedrock for sound business decisions, and PDQ provides data quality solutions designed to optimize crucial DQ dimensions such as accuracy, completeness, consistency, timeliness, validity, and uniqueness. 

PDQ empowers users to recognize, comprehend, and rectify data imperfections, fostering improved decision-making and governance. PDQ provides the user with out-of-the-box capabilities to measure data quality across data assets in the organization by applying data quality rules.
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PDQ houses over 150+ Out-of-box measures across health, frequency, distribution, and statistical categories with dimensions based on the criticality of data to improve accuracy toward business outcomes. 
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1. Navigate to Settings > Quality.

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2. Enable/disable a measure for any given asset at a platform level, before configuring an asset.

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While the platform includes more than 150 measures, it is not confined to this predefined set. Users have the flexibility to personalize their measures by employing either straightforward conditional arguments or a query mechanism. 

Custom measures can be created at an asset or attribute level depending on requirement.
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1. Open the asset > Go to properties > Click on the + icon at the top right corner of the measures table.

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Users can establish rules grounded in predefined conditional values, and PDQ additionally offer the capability to incorporate multiple conditional rules and rule groups within a single measure.
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PDQ enables users to employ native database queries for creating measures. 

For instance, users can utilize queries like "Select \* from Person.data where ID < 100" or employ joins to filter the data. The valid toggle buttons can be utilized to set the polarity of the results.
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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://academy.pentaho.com/data-quality-en/pentaho-data-quality/getting-started/measure.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.