Blog
Writing on data, AI & engineering
Practical insights from building and operating modern data platforms.
AITech Interview: Building Trusted DataOps Methodology
In this AITech Park interview, I discuss the origins of DataOps.live, the 7 Pillars of DataOps, and why data engineering needed its own DevOps moment. Originally published on dataops.live.
How to Make Your Data AI-Ready
Trusted data is the foundation of every successful AI initiative. Here's what AI-readiness actually requires. Originally published on dataops.live.
Unpacking Snowflake's Evolution on DevOps
How Snowflake's growing DevOps capabilities are transforming data operations — and why orchestration is the missing piece. Originally published on dataops.live.
AIOps and LLMOps: The Evolution of DataOps and Beyond
How the data management landscape evolved from pure DataOps into a converged ecosystem of DataOps, DevOps, and CloudOps — and what that means for AI. Originally published on dataops.live.
DataOps: A 10x Efficiency Boost and a Golden Opportunity to Be Disruptive
Why the smartest data teams use DataOps efficiency gains to innovate — not just to handle more tickets. Originally published on dataops.live.
Snowflake — The Best Time Series Database in the World?
After 20+ years working with time series data, here's why I believe Snowflake's flexibility beats dedicated TSDBs for most production use cases. Originally published on dataops.live.
Data Products Done Right: Delivering Value Now
Key insights from the Big Data LDN keynote panel on implementing data products that actually deliver business value. Originally published on dataops.live.
Data Products for Dummies: A Guide to the New Model for Managing Data
Co-authored with Sanjeev Mohan and Justin Mullen, Data Products for Dummies is a practical guide to treating data as a product. Originally published on dataops.live.