Are Semantic Layers the Cornerstone for AI Analytics?

This post discusses the role of semantic layers in AI analytics and argues for a broader approach to context. It critiques the limitations of semantic layers as the sole solution for AI governance and accuracy, proposing that a combination of semantic models, raw data transformation, and other contextual information (like code repositories, warehouse metadata, strategy documents, and customer interactions) is necessary for robust AI analytics. It highlights how Hex's agent leverages both semantic models and other contextual sources to provide more accurate and adaptable answers, and introduces Context Studio as a mechanism for capturing and governing this broader context.