This article reruns a 2023 benchmark with the latest LLMs, comparing direct SQL generation against querying through a structured dbt Semantic Layer. It finds that while text-to-SQL accuracy has jumped, a modeled Semantic Layer still delivers near-perfect, deterministic results for covered queries, making it ideal for complex or critical use cases.

This article discusses a live session with Alejandro Aboy, a Senior Data and AI Engineer, about the evolving role of data engineers in the context of AI. Alejandro emphasizes that strong data engineering skills, particularly data modeling and orchestration, are crucial for successful AI work and shares practical steps for integrating AI into existing data workflows.

This article explores the evolving role of data engineers over the past 50 years, highlighting their often unnoticed contributions to data infrastructure. It discusses the challenges they face, such as managing dependencies and schema changes, while emphasizing that the core problems remain unchanged despite new tools and technologies.

Since the inception of SQL in 1974, there has been a recurring dream to replace data analytics developers with tools that simplify the querying process. Each decade has seen innovations that aim to democratize data access, yet the complex intellectual work of understanding business needs and making informed decisions remains essential. Advances like AI can enhance efficiency but do not eliminate the crucial human expertise required in data analytics.