The Schema Strikes Back: Killing the Normalization Tax on the SOC | A Crogl Spotlight Brand Story Conversation with Cory Wallace

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Solving the Normalization Problem in Security Operations

Security teams today face a data management crisis. Logs, alerts, and telemetry come from every layer of the enterprise—from endpoints and firewalls to SaaS applications and cloud platforms. Each source speaks its own language, creating fragmentation and forcing teams to rely on normalization to make sense of it all. But normalization adds complexity, delays detection, and creates blind spots through schema drift. The result is a SOC struggling to manage both scale and accuracy.

Customer Challenges

  1. Data Fragmentation and Schema Drift

    Security data lives everywhere, often in inconsistent formats. Every time a vendor updates a log schema, mappings break and context is lost. Analysts are left chasing missing fields or outdated connectors instead of investigating threats.

  2. Analyst Fatigue and Overload

    With alert volumes skyrocketing, analysts spend more time translating data than interpreting it. Each system uses a different query language, adding cognitive load and training overhead that slow investigations.

  3. Inefficiency and Rising Costs

    The normalization process consumes storage, compute, and staff time. It’s a hidden tax on every investigation and an obstacle to scaling security operations efficiently.

The Solution: Query Without Normalization

Crogl’s patented technology eliminates the need to normalize data before analysis. Instead, it understands fields dynamically—recognizing and aligning identifiers such as IP addresses or user IDs across disparate systems automatically. This approach allows analysts to search and correlate across all data sources without schema dependencies or rigid mapping.

Business Impact

  • Faster Investigation and Response: By removing normalization steps, investigations start instantly with full context and history available in one place.

  • Reduced Training Requirements: Analysts no longer need to master multiple query languages or maintain fragile connectors.

  • Operational Efficiency: Fewer FTEs are required to manage data pipelines, freeing resources for proactive threat hunting.

  • Improved Accuracy: Eliminating schema drift ensures that updates or changes in log formats never obscure critical signals.

  • Empowered Analysts: Rather than replacing analysts, automation enhances their visibility and decision-making—turning every investigation into a learning opportunity.

Outcome

This shift redefines how SOC teams interact with data. Instead of normalizing and indexing, they query directly and intelligently. By addressing the root cause of inefficiency—data friction—Crogl enables a more resilient, scalable, and human-centered approach to security operations.
 

Learn more about CROGL: https://itspm.ag/crogl-103909

Note: This story contains promotional content. Learn more.

Cory Wallace, Director of Product Marketing at CROGL
On LinkedIn: https://www.linkedin.com/in/corywallacecrogl/

Learn more and catch more stories from CROGL: https://www.itspmagazine.com/directory/crogl


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