6d ago · 3 min read · We’ve explored the problems with "Vibe-based" engineering, the rise of the Cognitive Interface, and the immediate power of the apcore Adapter ecosystem. But as any experienced engineer knows, a standa
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Feb 24 · 3 min read · Getting ready for a meta data scientist interview at Meta can feel confusing when every blog or thread describes a slightly different process. You might already be strong in SQL and experimentation, y
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Feb 12 · 10 min read · Why Traditional Metadata Management Approaches Fail Legacy data catalog solutions built for on-premise data warehouses cannot handle the scale and complexity of modern data architectures. Traditional approaches relied on manual metadata entry, period...
Join discussionFeb 5 · 5 min read · At Uber, we had over 300,000 datasets, and most of them were unowned. Engineers couldn't find the data they needed, and when they did, they had no way to know if they could trust it. Who owned this table? Where did the data come from? What did the nu...
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Jan 26 · 1 min read · Ask most teams where their data comes from. They can’t tell you. That’s a metadata problem. What Metadata Includes Schema information Data lineage Ownership Feature provenance Model dependencies Without this, systems become opaque. Why Metad...
Join discussionJan 21 · 1 min read · Most AI programs don’t stall because the model is weak. They stall because teams don’t trust the data. In The Executive Outlook, Dr. David Marco explains why metadata, governance, and data quality are the layer that makes AI usable in the real world....
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