Agentic Control Center for Data Product Optimization

TL;DR

This paper introduces an AI-driven system that automates the creation and refinement of data products by continuously optimizing quality metrics, involving human oversight to enhance trust and effectiveness.

Contribution

It presents a novel agentic control center that automates data product enhancement through continuous optimization and human-in-the-loop controls.

Findings

Automates data product improvement using AI agents.

Balances automation with human oversight for trust.

Enhances data asset observability and refinement.

Abstract

Data products enable end users to gain greater insights about their data by providing supporting assets, such as example question-SQL pairs which can be answered using the data or views over the database tables. However, producing useful data products is challenging, and typically requires domain experts to hand-craft supporting assets. We propose a system that automates data product improvement through specialized AI agents operating in a continuous optimization loop. By surfacing questions, monitoring multi-dimensional quality metrics, and supporting human-in-the-loop controls, it transforms data into observable and refinable assets that balance automation with trust and oversight.