Business people leverage data for decision-making, sourced either publicly or from their company’s databases. However, when internal data is necessary, most lack the expertise in SQL, Cypher, or other database-specific languages. This creates a gap bridged by data analysts who act as business-to-database interpreters, translating human questions into the language the database understands.

These days, large language models (LLMs) like GPT or Mistral can fulfill some of the tasks performed by data analysts. For instance, LLMs can:

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