#data-architecture

#data-architecture

Large Language Models aren't the issue. They just do what they were designed to do, which is to generate plausible responses based on statistical patterns. They can write fluent paragraphs, summarize documents, and even mimic strategic thinking. But they don't reason, and they don't verify. They only guess. If a model says that Company A acquired Company B, it's not referencing logic. It's assembling words based on probability.

A metadata-driven ETL framework enhances scalability and security in integrating various data sources through Azure Data Factory, reducing manual rework.