#groundtruth

Jul 20, 2026

Ground Truth Before Go-Live: Building Better Fabric Data Agents with Automated Evaluation Datasets

One of the biggest challenges when building a Fabric data agent isn't creating the agent itself, it's knowing whether the answers it provides are consistently accurate. Many teams test a new agent by manually asking a handful of questions and reviewing the responses. While this approach can uncover obvious issues, it doesn't scale and it doesn't provide a reliable way to measure improvements over time. That's where ground truth datasets come in. A ground truth dataset is a collection of questions paired with known-correct answers derived directly from your semantic model. These datasets become the benchmark against which your Fabric data agent can be evaluated.