#data-scarcity

#data-scarcity

Developers have spent the past decade trying to forget databases exist. Not literally, of course. We still store petabytes. But for the average developer, the database became an implementation detail; an essential but staid utility layer we worked hard not to think about. We abstracted it behind object-relational mappers (ORM). We wrapped it in APIs. We stuffed semi-structured objects into columns and told ourselves it was flexible.

Organizations are drowning in dashboards, KPIs, performance metrics, behavioral traces, biometric indicators, predictive scores, engagement rates, and AI-generated forecasts. We have more data than we know what to do with. We pretend that the mere presence of data guarantees clarity. It does not. That's data hubris—the arrogant belief that because something can be measured, it can be mastered.

If you work in martech, marketing operations or related roles, you've surely heard colleagues and leadership complaining about data quality and their lack of trust in data. We often place the blame for data quality on the system, because we're not willing to fully say the quiet part out loud: The No. 1 factor in data quality is the people, the processes and the level of rigor in those processes.