
GenAI for the People: The IT Guide to Scalable AI Infrastructure | Dialpad
Ship all three together or you’ll bottleneck every downstream use case.Establish a governed, interoperable data foundation—lakehouse, lineage, and vector access—so analytics, ML, and GenAI workloads draw from consistent, well‑controlled sources.Lakehouse ≥ warehouse: Adopt an open-table-format lakehouse (Delta, Iceberg, Hudi) so analytics, feature engineering, and vectorization share one source of truth.Column- & row-level lineageEmit metadata (OpenLineage, Marquez) from every pipeline—ETL, ELT,...