Continuous Data Quality Dashboarding

Purpose

Continuous Data Quality Dashboarding is designed to build predictive dashboards showing trends in data quality issues and their potential impact on model accuracy, using historical data quality metrics and model performance indicators.

Primary users

The primary user is not specified in the provided information. The agent is associated with AQS and owned by Ronan Davit.

Where it fits (process/stage/trigger)

This agent fits into data quality monitoring and model performance review processes, where historical data quality metrics and model performance indicators are analyzed to understand issue trends and their possible relationship with model accuracy.

Key capabilities / workflow

The agent analyzes historical data quality metrics, extracts model performance indicators, evaluates whether the available information supports impact assessment, generates predictive dashboard views, and supports validation before delivering trends and potential impact insights.

Inputs

The specified inputs are historical data quality metrics and model performance indicators. Other input details are not specified.

Outputs / Deliverables

The specified deliverable is a predictive dashboard showing trends in data quality issues and their potential impact on model accuracy. Other output details are not specified.

Value

The value of Continuous Data Quality Dashboarding is to help surface data quality issue trends and connect them with possible model accuracy impact, supporting better monitoring and decision-making in an insurance context.