The core theoretical principle posits that data unification and governance must precede artificial intelligence implementation to prevent model degradation (garbage-in-garbage-out), operating within the domain of modern enterprise architecture. The mechanism relies on an "end-to-end" platform abstraction where distinct traditional boundaries between SQL, NoSQL, lakehouses, and analytics workloads are dissolved into a unified fabric governed by OneLake semantics. This framework establishes that organizational intelligence scales not through vertical stacking of tools but via horizontal integration of heterogeneous data sources into a single open table format repository powered by global semantic models.
The core theoretical principle posits that data unification and governance must precede artificial intelligence implementation to prevent model degradation (garbage-in-garbage-out), operating within …