Map raw security logs to OCSF in the Databricks lakehouse silver layer to end schema drift, cut SIEM ingest cost and speed threat hunting.
OCSF and the Silver Layer: Conforming Security Logs
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— Blog · The Discipline Layer for AI
Field notes on doing AI the disciplined way.
Contrarian, data-grounded essays on the three things that decide whether AI pays: a sharper problem, governed data, and demand that survives the answer-engine age.
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Growth · Featured essay
AI Content Generation: From Caves to Code
The first content strategists painted on cave walls. The newest ones orchestrate agents. This essay traces the whole arc — and shows how a disciplined content engine drove 359% organic traffic growth for a B2B client by treating generation as a system, not a shortcut.
Frank Shines & Umer Qureshi · Read the essay →
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Every post strengthens one of the three foundations — Problem, Data, or Growth.
Hive Metastore to Unity Catalog Migration: Plan, UCX and What Breaks
New Databricks workspaces lose Hive metastore access from 30 September 2026, while existing ones keep it. Here is how to plan the Unity Catalog migration, pick the right tool per table, and avoid the breaks.
Data Governance as a Measured Program, Not a Policy Binder
Policy binders do not stop bad data. See how governance coded into a Databricks lakehouse keeps AI pipelines and outputs trustworthy.
AI Agent Governance: The Audit-Trail Fields That Matter
The exact fields an AI agent’s audit trail needs, from the human who directed it to the downstream action it took, and the lakehouse table that produces each one.
Databricks Lakewatch: What the Agentic SIEM Changes for Security Data
Databricks Lakewatch is an agentic SIEM that runs on the lakehouse, built on OCSF and Unity Catalog. Here is what it changes for security data, and what it does not.
The Medallion Architecture Is Lean Six Sigma in Disguise
Bronze, silver, and gold are process control for your Databricks lakehouse. Here is how layered data engineering makes pipelines AI-ready.
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