Fields Quality & CIM Compliance

Automatically assess Common Information Model compliance for your Splunk data, ensuring security use cases and datamodel-dependent workflows work reliably.

Monitor fields quality for any data context, not just CIM. Define custom data dictionaries with fields of interest and track parsing accuracy across all your sourcetypes.

Create collect and monitor jobs through guided wizards. Two-phase workflow — collect samples, then monitor quality — running on configurable schedules with sampling or head strategies.

Build and maintain comprehensive data dictionaries — auto-generated from CIM datamodels or custom-defined for non-CIM contexts. Dictionaries are shareable across collect jobs.

Define quality thresholds at both the global entity and individual field level. Thresholds are initialized during entity discovery and easily adjustable per field.

Target the local search head or transparently assess fields quality on remote Splunk deployments — ideal for Enterprise Security environments and accelerated datamodel searches.

Preview CIM compliance results before committing. Benchmark collect strategies — sampling vs head modes — to choose the best approach for your environment.

Aggregate quality results per datamodel, index, sourcetype, or custom combinations. Create monitor-only jobs to re-use collected samples for different aggregation purposes.

Fields quality KPIs — compliance rates, parsing success percentages — are stored as high-performance metrics in the Splunk metrics store for fast historical trending.