Deep dives on pipelines, cloud architecture, data modeling, and the future of data infrastructure. Written from the trenches.
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Error handling, alerting, and retry strategies for real-world data pipelines.
How to cut your Snowflake bill by 40% without sacrificing performance.
IaC strategies that work across AWS, Azure, and GCP without going insane.
The gap between a Jupyter notebook and a real ML pipeline — and how to cross it.