Discover how to tame data volume and complexity to drive better cybersecurity and observability outcomes with the new rules of data management.
Data Challenges
Data management obstacles lead to real-world consequences
Organizations are struggling to find solutions to exploding data volumes and complexity. Yet many haven't evolved their data management practices, leading to increased costs, limited visibility, and reduced access.
- 91% report spending more on data management than in the previous year.
- 73% cite data volume as a primary driver for increased data management costs.
- 62% say data management challenges have led to compliance failures.
New Rules of Data Management
Modern capabilities shaping data management
Organizations that embrace modern data management practices are able to access data faster, overcome data volume challenges, and reduce costs.
- 67% of organizations with partial or full data federation report faster data access.
- 46% of organizations employing data reuse are less likely to face hurdles with high volumes of data, compared to 71% of other respondents.
- 50% of those using data tiering rank reduced storage costs as a top positive impact.
Enhance Security and Observability
Strong data management drives digital resilience
Being a data management leader — i.e. leveraging data federation, pipeline management, and lifecycle management — has a measurable outcome that improves security and observability.
- 79% of leaders report faster MTTR compared to 61% of other respondents.
- 43% of leaders cite fewer data breaches compared to 34% of other respondents.
- 79% of leaders confirm their data management strategy improved performance optimization for app infrastructure, compared to 60% of other respondents.
Driving AI Adoption
Data management boosts AI — and vice versa
A robust data management strategy can be a force multiplier for AI adoption and performance — but AI also enhances data management by accelerating productivity.
- 82% say their organization’s data strategy improves the accuracy of their machine learning models.
- 74% report their data management strategy helps remove bias from the data sets from which AI models learn.
- 73% of organizations say that AI has helped data quality enhancement by automating repetitive tasks.
