The data trap most AI companies fall into

Are data lakes helping AI or quietly breaking it?

David Bauer explains why data lakes often turn into data swamps. As companies centralize enterprise data, problems like data duplication, data governance, data quality, normalization, and data processing can make AI models, AI agents, machine learning systems, and LLMs less effective in production.

The biggest AI mistake? Training on perfect datasets instead of real production data.

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