Chief data officers, VPs of data platforms, and data engineers are dealing with a significant lack of visibility into the complex data stacks they manage, according to a report from data observability provider Acceldata.

The survey, which was conducted by Censuswide, reached more than 200 data executives and revealed one-quarter of those questioned stated a lack of data visibility is a major data management pain point. Of the overall group, 45% experienced data pipeline failures between 11 and 25 times in the past two years as a result of errors or poor data quality. More than 20% of data execs had those issues 10 times or more in that time, and 18% experienced data pipeline failures between 26 and 100 times.

Data pipelines enable the movement of data and support customer experience, which should render observability at this layer an enterprise priority. A majority (63%) of execs dealing with data networking pipeline failures noted those issues negatively impact their organization's customer experience.

"For those who dealt with multiple data pipeline failures, we can presume that these customer experience issues created ongoing issues that required immediate attention across many data team members," the report reads.

Data quality issues also affect an enterprise's time resources, with 53% of data execs reporting up to six days each month are spent dealing with poor data quality. And a significant majority (90%) consider data quality issues an inordinate time suck.

The research shines a light on discrepancies between data management issues and strategies. A large majority of respondents said they're satisfied with the data management tools at their organization, and 40% are convinced they have viable data networking pipeline observability tooling – which the report noted is "especially concerning."

The survey also found one-third of those questioned cited the cost of data tooling and whether or not the organization is getting the most bang for its buck as a top concern. Additional concerns included a lack of data visibility (25%), data quality (18%), and the inability to manage sophisticated data networking pipelines (10%).