The effort and expense needed to get value from data—not just storing it, but cleaning, structuring, and analyzing it. Cheap-to-store data can still be expensive to analyze, which shapes how useful it actually is.
It was cheap to fill the data lake, but the analysis cost—engineers, tools, and time—made most of it unusable.
