About

Jeremy Wiley.

Cybersecurity architect and data scientist focused on security data architecture and emerging-tech research. The opinions on this site come from operating the platforms in production rather than consulting about them, and from a research portfolio where I keep the contradictions on the record when new evidence overturned a prior position.

Why this practice exists.

Most security data programs trust their vendors, their schemas, and their own past assumptions. The data platform should have to earn that trust empirically, source by source, claim by claim, query by query, and keep earning it, not just at procurement time. That is the whole reason this is a single-practitioner fair-broker practice rather than a reseller or a staff-aug shop: no reseller margins, no vendor-paid placements, open methodology, and an annual external review. The disclosures below are the structural commitments that keep those words honest. The longer argument is on the thesis page.

Fair broker is not a tagline; it is the constraint the practice is built around. A senior practitioner billed by the hour to extend a vendor's services arm cannot give a vendor-neutral recommendation, because the incentive is to keep the engagement running. Fixed-price, scoped, and evidence-gated is the alternative I run on instead.

Practitioner depth.

Twenty-five years across military service, intelligence-community analytics, and security data engineering. The most recent work is an embedded resident-engineer assignment with a Tier-1 financial-services security-data team, via Corelight: production reference-architecture work for a regulated environment, not a slide deck about one.

• Corelight. Professional Services Engineer, building international customer reference architectures. This is where the Data Health Check and Data Health Enablement methodologies that gate the engagements were shipped.
• Southern Company. Senior Security Architect and Security Data Scientist on a regulated OT estate.
• Accenture. SIEM migrations in regulated environments.

The pattern across all three is the same: large, regulated, multi-source security data, where the cost of a wrong architecture decision compounds quietly for years before anyone names it.

Contributor to OCSF (the open schema standard) and ITU-T Study Group 17 (the international standardization work building on it), both of which show up directly in the recommendations this practice makes. The research surface keeps documented contradictions where a prior position was overturned on contact with new data; that update history is public on the research page rather than quietly revised.

U.S. Marine Corps veteran. Atlanta Metro.

Wrote Modular Open Architecture (MOAr) for Cybersecurity Data, manuscript complete, in production, Amazon KDP.