Practical takes on data engineering, building scalable systems, and what it really takes to run production platforms
Insights from our team of data platform experts
Session handoffs waste 10,000+ tokens re-explaining context. Learn how to build an MCP server that implements a Handoff Protocol to reduce context transfer to under 2,000 tokens.
Every wasted token in your AI coding workflow is money out of your budget. Learn to identify token waste, measure its true cost, and understand the hidden productivity costs.
Hard-earned insights from building production data pipelines at scale. Learn about common pitfalls, architecture patterns, and best practices that actually work in the real world.
ADF is a solid starting point for Azure data integration - but it's not built for every workload. Learn the real-world limits teams encounter in production and when to evolve beyond it.
Tech debt in data platforms compounds faster and costs more than in traditional software. Learn to identify, measure, and tackle the hidden costs that are slowing down your data team and business.
Learn how to build a modern data stack from scratch, covering architecture patterns, tool selection, and best practices for data platform engineering.
The medallion architecture has become the default pattern for data lakes, but it's not a silver bullet. Learn the real-world pitfalls teams encounter and how to avoid them.
Essential monitoring, alerting, and debugging strategies for modern data platforms. Learn how to implement comprehensive observability for your data infrastructure.