Use Case
Eliminate stale and shadow data
60-90% of all data goes unused, or dark, quietly accumulating in the cloud. Some of this neglected data has gone stale, expanding an organization’s data surface while increasing its cost and risk. Other times data is copied and simply forgotten in the rush to get a project completed, creating shadow resources that hide in plain sight.
All pain, no gain
Needlessly large data surfaces always cost more than they should. They also run counter to compliance mandates such as GDPR data minimization, which states you must only keep data for as long as it is necessary for the purpose for which it was collected. Further, shadow and stale data are frequently found after a serious leak or breach, such as the infamous Equifax incident. The sensitive data we know about we lock down. The rest drives needless risk and costs.
Bright lights from a big map
It’s simply been too much effort to spot shadow data in the past. Open Raven automatically maps cloud resources while pinpointing native and non-native data services so that they are plainly visible. Forgotten data stores, unwanted peering relationships and dangerous external connections are visually displayed within minutes of setup allowing for quick results before data is even analyzed. The map also provides an effortless response to demands for reporting out data locations during audits or other compliance initiatives.
Pinpointing stale resources
Open Raven also scores data stores using a staleness rating that makes it straightforward to spot unnecessary resources and data that can be safely removed to drive down cloud risk and your monthly bill. Stale data repositories, whether an old S3 bucket or geriatric RDS instance, appear as alerts alongside related problems, such as production data found in a test environment. A single, unified workflow that integrates with ticketing, Slack, or via webhook streamlines remediation.
