# Quality

{% hint style="info" %}
Users can navigate to Quality under Settings to view all of the out-of-the-box measures categorized under Reliability, Distribution, Frequency, and Statistics.&#x20;

They can select whether the measure is:

&#x20;  ● Active or Inactive,&#x20;

&#x20;  ● Valid or Invalid,&#x20;

&#x20;  ● Include it in scoring

&#x20;  ● Monitor&#x20;

Best practice to use the quality page:

&#x20;  ● Document the requirement/business case for each asset or a business as a whole&#x20;

&#x20;  ● Identify the Out of the measures from the below-mentioned section, and enable them before conﬁguring an asset&#x20;

&#x20;  ● Ensure to choose scoring/monitoring on a need-to-basis&#x20;

&#x20;  ● Conﬁgure the assets after the settings to auto-enable the selected measures for any asset that is conﬁgured in the platform
{% endhint %}

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{% tabs %}
{% tab title="Reliability" %}
{% hint style="info" %}
Deﬁne health-related measures to measure data reliability or health check of the dataset. These map back to the [DAMA](https://www.dama.org/cpages/home) six pillars of Data Quality.&#x20;

Obviously you can add your own Custom Dimensions.
{% endhint %}

<figure><img src="https://content.gitbook.com/content/7w2PGGr7BR8BUW5guKgZ/blobs/AUlvL2f5BxWSu96HpXCu/image.png" alt=""><figcaption><p>Reliability checks</p></figcaption></figure>
{% endtab %}

{% tab title="Distribution" %}
{% hint style="info" %}
Aimed toward the Data Analyst or Data Steward who are concerned with, for example, character checks, character distribution at the column level.  Basically checks to measure and understand the content of data assets.
{% endhint %}

<figure><img src="https://content.gitbook.com/content/7w2PGGr7BR8BUW5guKgZ/blobs/fYVnc2lvmpEd4I6BaaXR/image.png" alt=""><figcaption><p>Distribution rules</p></figcaption></figure>
{% endtab %}

{% tab title="Frequency" %}
{% hint style="info" %}
Deﬁne frequency-related measures to understand the format and enumeration of data assets.
{% endhint %}

<figure><img src="https://content.gitbook.com/content/7w2PGGr7BR8BUW5guKgZ/blobs/N2piCChMF5rp5GQ7iICY/image.png" alt=""><figcaption><p>Frequency rules</p></figcaption></figure>
{% endtab %}

{% tab title="Statistics" %}
{% hint style="info" %}
Deﬁne statistics-related measures to ﬁgure out the suitability of the data for its intended applications in data analytics, data science, or machine learning.
{% endhint %}

<figure><img src="https://content.gitbook.com/content/7w2PGGr7BR8BUW5guKgZ/blobs/fO7N8e78QNg1XjRJPt39/image.png" alt=""><figcaption><p>Statistics rules</p></figcaption></figure>
{% endtab %}

{% tab title="All" %}
{% hint style="info" %}
Shows all the out of the box measure under one table.
{% endhint %}

<figure><img src="https://content.gitbook.com/content/7w2PGGr7BR8BUW5guKgZ/blobs/w3ogqxaolWIygX5g8VAG/image.png" alt=""><figcaption><p>All the rules</p></figcaption></figure>
{% endtab %}
{% endtabs %}
