TLDR: NEW YORKâMiroâs Snowflake agents missed the right joins over 65% because context was missing. DataHub now mines SQL query history to index proven joins for agents.
Key Takeaways:
- Miro tested Claude based agents against Snowflake and hit routing failure across 10,000 tables without a semantic guide.
- DataHub will release Context Intelligence Thursday, building a semantic index from validated SQL query history and exposing it through MCP and agent frameworks.
- Instead of guessing from raw schema, agents retrieve âsemantic anchorsâ from golden queries, with domain experts resolving conflicts before publishing.
âHallucinated joinsâ is starting to sound less like a model flaw and more like bad plumbing. DataHub is basically turning years of analysts trial and error into a runtime compass, so agents can stop improvising.
âHallucinated joinsâ is starting to sound less like a model flaw and more like bad plumbing. DataHub is basically turning years of analysts trial and error into a runtime compass, so agents can stop improvising.
Q&A
If query history reflects past mistakes, how does a semantic index avoid encoding bad joins forever?
DataHubâs approach relies on filtering for âgolden queriesâ and human validation in Context Hub, including flagging conflicting metric definitions for review before updates.
Why does raw schema fail specifically for âjoin routing,â even when table names look obvious?
Schema says what exists, not what business question it answers. DataHub maps query history patterns into semantic anchors so agents pick the entities that previously solved the same intent.
What happens when teams change definitions and the old join logic stops matching reality?
A continuously refreshed semantic layer can reindex newer validated queries, while Context Hub surfaces disagreements and lets experts resolve conflicts before the runtime index is used.
Could platform specific tools replace this, or is the integration strategy the point?
DataHub positions the layer as platform neutral by provisioning context into existing endpoints like Snowflake semantic views and Microsoft Fabric IQ rather than forcing a single replacement system.
Why might governance teams care more than developers here, even though the product targets agents?
Lineage tracking and audit readiness depend on trusted context. When agents reuse validated joins, it changes how consistently decisions and reported metrics match governance expectations.
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