Graylog GO logo

Feature

Data Enrichment

Data enrichment allows for the incorporation of valuable context to existing logs and security events to enhance security operations. Rich context improves risk scoring, readability, search and data visualization. This provides additional context to improve risk scoring, make the data more human-readable, and provide additional search and data visualization options.

Events & Alerts

How It Works:

Data enrichment has the ability to add multifaceted context to your logs. By integrating different types of contextual information—such as user identity, geographical location, and device specifications—and adhering to standardized schema across all log sources, this feature ensures unparalleled aggregation. This standardized approach to data collection and enrichment allows for a cohesive analysis, offering comprehensive insights into your systems’ performance and security.

Data Enrichment Data Adapters

Data enrichment not only simplifies the complexity inherent in diverse log data but also elevates the intelligence of your analytics.

Learn More About Data Enrichment

Data enrichment enhances analytics by adding context to log data, which helps in identifying and mitigating potential security threats more effectively, thereby reducing risk.

Lookup tables are used in data enrichment to add additional information to log data, such as user details or asset information, providing a richer context for analysis.

Linking assets within an enterprise allows for the correlation of log data with specific assets, offering insights into how different components interact and potentially impact security and performance.

Adding context to logs, such as geographical information or device details like hostnames or ever-changing IP addresses, enables more detailed analysis, improving threat detection and operational insights in log management.

A standardized schema ensures consistency in how data is formatted and enriched across all log sources, facilitating better aggregation, analysis, and insight derivation.

By enriching log data with additional context and maintaining a standardized format, data enrichment allows for more effective aggregation and analysis, leading to deeper insights and improved system oversight.