Data quality

The data quality dashboard allows for analyzing the changes in missing and unseen values over time. Here is our guide explaining how to use the data quality dashboard:

There are three main components of the Data quality dashboard:

1. Filters

Filter which data quality metrics you want to see. Data quality metrics that are not calculated are not visible under the filter. Selecting which data quality metrics you want to calculate can be done under model settings.

Note that unseen values do not apply to continuous columns. It is typically used to assess if new categories are appearing on which the model was not trained.

2. Visualisations

You can change the order of charts based on the metric name, number, or recency of the alerts.

3. Plots

There are two types of plot formats: line and step. A line plot smoothly connects points with straight lines to show trends, while a step plot uses sharp vertical and horizontal lines to show exact changes between points clearly.

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