<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Knowledge Graph on DataAgentX</title><link>https://e343c64b.dataagentx.pages.dev/en/tags/knowledge-graph/</link><description>Recent content in Knowledge Graph on DataAgentX</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Tue, 08 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://e343c64b.dataagentx.pages.dev/en/tags/knowledge-graph/index.xml" rel="self" type="application/rss+xml"/><item><title>Why Stronger Data Agents Need a Semantic Layer</title><link>https://e343c64b.dataagentx.pages.dev/en/tech/20260908-semantic-layer-for-data-agent/</link><pubDate>Tue, 08 Sep 2026 00:00:00 +0000</pubDate><guid>https://e343c64b.dataagentx.pages.dev/en/tech/20260908-semantic-layer-for-data-agent/</guid><description>&lt;p&gt;Give a model the schemas for orders, payments, and customers and it can quickly produce executable SQL. Ask “What was revenue last month?” and the real work begins. Does revenue mean booked value, cash received, net receipts, or recognized revenue? Which date applies? In which period do refunds belong?&lt;/p&gt;&#10;&lt;p&gt;Those are not universal facts for a model to infer. They are enterprise contracts. As an agent gains tools and a longer execution chain, the cost of propagating one incorrect definition into a report or action increases.&lt;/p&gt;</description></item></channel></rss>