The key findings of the survey of 314 big data professionals are: - 87% said 'bad data' pollutes their data stores and 74% said 'bad data' is currently in their stores. Ensuring data quality was the top challenge cited. - 72% build data flows through hand coding while 53% change pipelines several times per month. - Only 12% rated their ability to detect issues like stopped pipelines or degraded performance as 'good' or 'excellent'. - There are significant gaps between the real-time visibility needed and what current tools provide across metrics like error rates, divergent data, and privacy detection. - 81% said upgrading big data components has significant operational impact.