
Data Engineering: Architecture and Tool Selection
This post is on architecture and choosing your tools for the Data Engineering Lifecycle

Early Data Engineering: Quick Wins, Not Wizardry
I’m kicking off a year-long read and build combo-wombo. First takeaway from Fundamentals of Data Engineering: data isn’t a magic trick—it’s a lifecycle. Generate > ingest > transform > serve > learn.

What I’ve Been Doing on PTO: Learning, Side Projects, and AI Experiments

Parsing Logs with AI: A Systematic Approach to Log Analysis

Embracing the AI Journey: From Prompting to Automation
