In 2021, semantic layers took the data world by storm. Since then, companies have been built (and some have failed) on the promise of the semantic layer, blog posts have debated their rise and fall, and data teams are still left wondering: was it all just hype, or are semantic layers the next big thing in data? I'll explore the evolution of the semantic layer, how they solve key problems for data teams today, and answer the burning question: are they here to stay, or just a passing trend?
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