← This weekAnalysisData engineering & the warehouse/lakehouseThe article questions whether the rush to adopt complex AI systems is overshadowing the need to address fundamental data discoverability issues. It suggests that focusing on improving data quality and accessibility should take precedence over deploying advanced AI technologies.
MyDataWork POV — Chasing after complex AI solutions without first addressing basic data discoverability is like building a skyscraper on sand. The appeal of AI is clear, yet without strong data foundations, these systems risk turning into complex noise generators. The real urgency lies in cleaning up the fragmented data environment. It's not glamorous, but ensuring data quality and accessibility is the bedrock for any meaningful AI application. Let's fix the basics before layering on the complexity.
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