<ul><li>Large language models have mastered Text-to-SQL in public databases, accurately generating SQL queries.</li><li>Language models, known as LLMs, struggle in enterprise data engineering due to cryptic abbreviations used in enterprise systems.</li><li>LLMs excel in public datasets with descriptive column names, while enterprise systems have cryptic abbreviations.</li><li>The knowledge gap created by cryptic abbreviations in enterprise systems poses a challenge for even advanced language models.</li></ul>

The Limitations of LLMsin Enterprise Data Engineering

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