Why Your Data Lake Needs BLM, Not LLM

Author(s): MKWriteshere

Originally published on Towards AI.

The “Godfather of Data Warehousing” reveals why LLM can’t solve enterprise text analytics.

Your $15+ billion data lake investment just became a liability.

This article highlights the failures of current approaches to data lakes, emphasizing that 85% of big data projects fail due to the inability to extract meaningful insights from textual data. Authored by Bill Inmon, the piece criticizes the over-reliance on generic language models, such as ChatGPT, which do not cater to specific industry needs. Instead, it advocates for Business Language Models (BLMs) that focus on industry-specific vocabulary and contextual intelligence, offering a more targeted and cost-effective solution to transform unstructured data into structured, actionable insights.

Read the full blog for free on Medium.

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Published via Towards AI