Data Quality Reporting

This article describes how you can leverage data quality (DQ) metrics from ONE in ONE Reports.

Thanks to data quality reporting, you can customize views and aggregate data quality across multiple catalog items for more comprehensive insights. This way, you can create engaging narratives, boost data credibility, and use your reports as a decision-making tool.

Before proceeding, take a moment to get familiar with how data quality is evaluated in ONE:

one-reports:getting-started:get-started-with-data-quality.adoc - An overview of the key features of Ataccama ONE Data Quality.
one-reports:data-quality:data-quality-overview.adoc - A deep dive into all there is to know about data quality in ONE.

Available DQ metrics and views

As outlined in Build a Visualization, you can incorporate DQ results as out-of-the-box datasets when creating a new visualization (Select datasets > Data Quality results).

The following sections provide more details and examples of different types of DQ metrics that you can employ in ONE Reports.

data quality reporting create a visualization data quality results wizard

Catalog items - Overall quality

In Data Quality results, select Catalog Items - Dimension quality to inspect the health of individual catalog items and highlight which areas require remediation.

Example: Consider a bar chart featuring two dimensions: catalog items and the processing start time, which allows you to track changes over time.

The metrics indicate the number of failed records for each catalog item over a specified period.

data quality reporting catalog items overall quality

Catalog items - Attribute-level DQ

In Data Quality results, select Catalog Items - Attribute quality to assess data quality on attribute level within a specific catalog item.

Example: Visualize a category chart where dimensions list attributes within a single catalog item and the metrics measure the record quality as passed or failed, as well as the quality ratio.

Color-coding is used to highlight the percentage of failed and passed records: green for passed and red for failed.

data quality reporting catalog items attribute level dq

Catalog items - Rule instance DQ

In Data Quality results, select Catalog Items - Rule quality to evaluate the data quality of records based on the specific rules applied to them.

Example: Think of a category chart featuring two dimensions: rule instances and specific catalog item attributes.

Metrics indicate the total number of failed records, with color codes indicating the volume of records failing each applied rule.

data quality reporting catalog items rule instance dq

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