The Doctor Is In: Why Data Health, Not Data Cleanup, Defines Enterprise Readiness in 2026
The traditional approach to data quality focused on fixing isolated issues, but this is inadequate in today’s complex environments. Organizations face significant financial losses due to poor data quality, with reliance on automated systems increasing. A new focus on monitoring pipeline health through behavior signals is crucial to maintain data reliability and trust.



