Data Quality Scores Dashboard

The Data Quality Scoreboard serves as a metric to assess the overall quality of a dataset, evaluating its compliance with specific standards like completeness, accuracy, consistency, timeliness, and relevance. Users can analyze data quality using metrics provided by the scoreboard.

The Data Quality Scores Dashboard offers an Overall Scores View and a Detailed Scores View.

Overall Scores

The Overall Scores provide a high-level overview of data quality scores for various schemas at the connector level.

• Donut charts represent the aggregate score for all child objects within a schema.

• Tooltips display object names and last updated timestamps when hovering.

• Clicking an object name leads to the Detailed Scores View for detailed exploration.

Detailed Scores

The Data Quality Detailed Scores provide insights into the overall health of selected data objects through multiple chart representations: Users can select specific tables and files within the Data Quality Scoreboard to view detailed data quality scores on the right side.

The Overall Data Quality Score gauge chart visually summarizes the data quality health of the selected object. The gauge score is calculated based on the Data Quality Rules Score, Child Score, Profile Score, and Service Request Score. The formula and calculation details are displayed in the Score Calculation pop-up. Use this chart to quickly assess the overall health of the data and determine whether immediate action is required.

The Data Quality Score Trend area chart provides a visual representation of how the data quality score evolves over a specific time period. This chart is designed to help users understand the historical performance and identify trends or anomalies in data quality.

• The X-axis represents the time intervals chosen by the user, such as days, weeks, or months. Users can customize the time range to focus on specific periods of interest, such as recent months or past years.

• The Y-axis displays the DQ Score, which ranges from 0 to 100. A higher score indicates better data quality, while a lower score highlights potential issues or areas requiring attention.

This visualization allows users to make informed decisions about maintaining or improving the quality of their data over time.

The Data Quality Metric Scores horizontal bar chart displays the scores for key metrics associated with the selected object. The chart provides both the numerical values and bar representations for the Data Quality Rules Score, Child Score, Profile Score, and Service Request Score. The Service Request Score is highlighted in red, indicating that higher values have a more negative impact on the overall Data Quality Score. Use this chart to compare individual data quality metrics and identify areas requiring improvement.

The Dimension Metrics Overview donut chart provides a detailed breakdown of the overall Data Quality (DQ) Score by key dimensions associated with the selected object. Each segment of the donut represents a dimension.

Interactive Pop-Up:

• Users can click the View Trend link for any dimension to explore its historical performance in detail.

• This action opens a pop-up displaying an area graph, which shows the dimension's performance trend over a selected time period (e.g., days, weeks, months).

• This visualization serves as a powerful tool for evaluating and improving data quality at a granular level.