Rising costs, compliance issues, and poor decisions due to outdated data strategies were some of the struggles impeding optimal data monetization.

Based on a survey of 1,475 IT, engineering, and cybersecurity professionals from November 2024 through January 2025* on data management topics commissioned by a cybersecurity and observability platform, several trends were discerned from the data.

First, 91% of respondents had cited increasing their data management spending compared to the previous year, while 67% among this group had reported that data volume and growth were posing a significant challenge to implementing their data strategy.

Second, 71% of respondents had indicated that difficulties in data management led to poor decision-making, with 40% citing a significant impact and 31% a moderate impact, while 62% had cited experiencing compliance failures: 33% reported significant issues and 29% moderate issues.

Other findings

Third, 69% of respondents had identified maintaining data security and compliance as a top obstacle, slightly ahead of data volume concerns. Also:

  • 59% of respondents cited that their organizations’ data management strategies had worsened data duplication, with 20% noting a significant increase, exacerbating inefficiencies and costs.
  • 53% had cited having to log into different platforms to access various data sources; 13% and 11% included unified visibility and accessibility, respectively, in their strategies.
  • Respondents whose organizations had fully implemented data federation, pipeline management, and lifecycle management — termed data management leaders — reported 79% improved mean time to respond, compared to 61% for others; 62% of such leaders had cited achieving cost savings, versus 34% for others.
  • 85% of respondents had indicated their data strategy provided sufficient volume and variety for AI-driven insights, and 82% noted improved accuracy in machine learning models.

The survey was commissioned by Splunk, whose data findings report concluded that legacy data management strategies are no longer enough in the AI era, and that forward-thinking approaches are essential for optimizing data value and enhancing digital resilience.

*respondents were from Australia, France, Germany, India, Japan, New Zealand, Singapore, the United Kingdom, and the United States. They represented 16 industries: business services, construction and engineering, consumer packaged goods, education, financial services, government (federal/national, state, and local), healthcare, life sciences, manufacturing, technology, media, oil/gas, retail/wholesale, telecom, transportation/logistics, and utilities. Respondents defined as “data management leaders” hailed from organizations deemed to have applied fully implemented data federation, data pipeline management, and data lifecycle management.