View Quality Scores

Quality Score builds on the analysis types you've configured for an Object (such as Fill Rate, Negative Value Analysis, etc.) and combines their results into one quality score per record, from 1 to 100. The result is a quick, trackable indicator of data health, that is shown on the object and field pages in the Monitor Library, directly on record pages in the lightning component, and in a PDF report.

• Quality Scores are calculated only when a Configured Job runs. Ad Hoc jobs return their own analysis results but are not saved in the Monitor Library, so they do not feed into the Quality Score.
• Quality Score results at the object and field level are aggregate. They do not show which individual records are pulling a score down; use the Record Quality component for that.
• Because scores only update on the next Configured Job run, expect a delay between changing an importance weight and seeing it reflected.

For information on how to enable and configure Quality Score for objects and fields, see Quality Score.

Monitor Library

Object and field score badges

Every object and field with Quality Scoring enabled shows a Data Quality Score badge with the current score out of 100 and a comparison to the previous analysis job (for example, "No change vs previous"). This badge is displayed in the Monitor Library, on the object and field pages, in the title section at right.

Trend chart

The Quality Trends tab on Object and Field pages in the Monitor Library shows a trend chart plotting the quality score over time. Red dashed lines on the chart mark the dates when scoring weights were changed. Scores on either side of a line are not directly comparable, since they were calculated against different weights.

Narrow the chart to a specific period using the date range filters above it (All time, This Year, This Month, This Week, or a custom range). Hover over a dot on the trend line to see the scoring details at that point in time.

Fields table

Below the trend chart on the object's Quality Trends tab, a Fields table lists every field with its Previous score, Current score, and Trend. A dash means no score is available yet for that field.

Object Configuration

Trend chart

The Quality Score tab in an object's Configuration shows a trend chart plotting the score over time. Red dashed lines on the chart mark the dates when scoring weights were changed. Scores on either side of a line are not directly comparable, since they were calculated against different weights.

Quality Scoring section

The field list in the Quality Scoring section of the Quality Score tab shows each field's Field Importance (as a 0 to 5 pip scale), and current Quality Score. Fields with their Field Importance set to 0 are excluded from scoring and display 'Not scored' instead of a score.
Expand a field to see the Analysis Importance pips for each of its configured analysis types.

A small green checkmark next to a field's name means the field has a Description filled in on its Salesforce field metadata, which earns it the fixed 10% documentation credit toward its score. Filling in descriptions for your most important fields is a quick way to raise their contribution. This is done in Salesforce Setup, in each field's Field Information settings.

Record Page Component

Reading the record page component

If a record page has the Quality Score Lightning component added, it displays on individual records as a Record Quality section. It shows:

• The record's current score out of 100, with a colored quality progress bar.
• A list with suggestions for quality improvement, such as empty fields, or fields still set to a default value.
• The date when the score was last calculated, and when the next update is planned.

Quality Score PDF report

After a Configured Job finishes, Plauti Monitor emails a PDF report to the user who ran the job. You can also download it after the job finished: on the Monitor Job Overview page, open Job Options menu for the job and select Download Report.

The report opens with the object's overall score, a plain-language summary, and an overview of the object analyzed, the number of records, and the number of issue areas found. It then lists one section per analysis type with a result worth flagging, ordered by priority, each naming the affected fields, the specific finding, why it matters, and a recommended action.