Data Foundations for AI: Owning Your Data in Open Formats

AI is only as reliable as the data beneath it. Fragmented, ungoverned data produces conflicting numbers and failed models. This paper makes the case for a single lakehouse — on Databricks, Snowflake or Fabric, in open formats you control — so that reports agree, AI projects stop failing at the data layer, and you own the asset rather than renting it from a vendor.

It covers the build sequence: inventory and profile the sources, model the highest-value domain first, stand up governed pipelines in Iceberg or Parquet, and extend domain by domain with ownership and quality standards defined up front.

Because the foundation is in open formats, the data stays portable — the investment is yours to move, not a trap.