Customers are pulling data back into the Oracle database as agents demand real-time access
A shared semantic layer is fast becoming the dividing line between lakehouses built for reporting and those built for artificial intelligence. As AI agents join human analysts in querying corporate data, enterprises need platforms that make sense of information scattered across clouds, formats and rival systems. Oracle Corp. has spent the past year rebuilding its […] The post Customers are pulling data back into the Oracle database as agents demand real-time access appeared first on Silico
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As AI agents increasingly access corporate data alongside human analysts, enterprises need platforms that can quickly understand and retrieve information scattered across different cloud systems and databases. A shared semantic layer is becoming essential to distinguish data platforms built for traditional reporting from those designed to support AI. Real-time data access has become more critical because AI agents request information on demand rather than relying on scheduled data refreshes that work for human users. One vendor is positioning its lakehouse platform as an open layer that queries data in place across multiple existing systems rather than copying it, allowing enterprises to maintain multiple data sources and platforms simultaneously.
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