The SecDataOps Revolution: Why Security Data Needs Its Own Pipeline

Security Data Is Broken. It’s Time to Fix It.

Security teams today don’t just face threats—they face data chaos. Logs, alerts, network traffic, and threat intelligence flood in from all directions. SIEMs demand structured data, analysts need enriched context, and leadership wants lower costs—all while attackers keep evolving.

Yet, security teams lack efficient data pipelines to make sense of it all. Instead, they rely on rigid, vendor-controlled ingestion models that are:

• Expensive: SIEM costs balloon when security teams can’t filter or preprocess data upstream.

• Inefficient: Manual enrichment, normalization, and correlation slow down investigations.

• Inflexible: Security teams struggle with custom parsers, brittle integrations, and siloed formats.

Meanwhile, other industries have already solved this—with DataOps.

What Security Can Learn from DataOps

The DataOps movement revolutionized how data is managed, transformed, and delivered across organizations. It introduced pipeline automation, dynamic data transformations, and as-code workflows—concepts that security operations desperately need.

SecDataOps applies DataOps principles to security, ensuring that security data is:

• Streamlined: Security data should flow like a real-time pipeline, not a messy pile of logs dumped into a SIEM.

• Automated: Normalization, enrichment, filtering, and correlation should happen dynamically, reducing analyst workload.

• Composable: Security teams should be able to build, extend, and modify their data workflows using modular pipelines.

• Open & Interoperable: Just as DataOps embraces open standards (Apache Arrow & Parquet), SecDataOps must do the same—ensuring security teams aren’t trapped in proprietary ecosystems.

The result? More efficient, cost-effective, and scalable security operations.

How Tenzir Brings DataOps to Security

Most security data pipelines today are SIEM-centric, meaning they focus on ingesting everything first, then filtering later—an outdated and costly approach. Tenzir flips that model.

With Tenzir’s security-native data pipelines, security teams can:

• Process data dynamically before it reaches a SIEM, reducing ingestion costs.

• Normalize, enrich, and correlate data in motion, not after it’s stored.

• Route data efficiently across security tools, ensuring the right data reaches the right place.

• Leverage open standards like Apache Arrow, eliminating lock-in and improving interoperability.

Why Tenzir?

✅ Security-Native Pipelines: Automate OCSF mappings, threat intelligence enrichment, and asset inventories—with built-in operators for Sigma & YARA rule execution.

✅ Full Data Ownership: No black boxes, no vendor lock-in. Security teams define where, how, and when their data flows.

✅ Cost-Efficient Operations: Reduce SIEM ingestion costs by filtering out duplicates, noise, and irrelevant data—before it ever gets stored.

✅ Composable & Open: Built on Apache Arrow and an open-core model, ensuring seamless integration with modern analytics and detection tools.

✅ As-Code & Interactive: Tenzir Query Language (TQL) makes pipeline composition effortless—whether for ad-hoc data exploration or as-code deployments.

The Future of Security Data is SecDataOps

The security industry is shifting away from monolithic SIEM architectures and toward composable security data fabrics. To keep up, security teams need:

• Real-time data automation, not manual enrichment workflows.

• Security pipelines built on open standards, not locked behind proprietary formats.

• A data-first approach, ensuring security teams control their data—not vendors.

At Tenzir, we’re not just building another tool—we’re bringing the power of DataOps to security.

Ready to take control of your security data? Get started for free and dive into our documentation to learn more.