This newsletter hits on a critical theme: data quality and reliability. We recently had a vivid example of this "Upstream Observability" problem. Our analytics dashboard reported a total failure for a new Microsoft Teams app launch: 1 visitor, 1 visit, 1 pageview. It looked like a complete flop.
But we dug into the raw logs (the upstream ground truth) and found a totally different reality: 159 events from 121 unique visitors, with a 31.4% share rate. The dashboard was hallucinating a 12,000% error.
It's a stark reminder: Don't trust the dashboard; trust the pipeline. If you're not observing your data at the source, you're flying blind.
The benchmarks comparng DuckDB, Polars, and Daft on 650GB are eye opening. DuckDB finishing in 16 minutes vs PySpark taking over an hour really shows how single node engines have evolved. Netflix's aproach to knowledge graphs and Uber's I/O observability work are also fasinating reads. Thanks for curating such valuable contnt every week.
This newsletter hits on a critical theme: data quality and reliability. We recently had a vivid example of this "Upstream Observability" problem. Our analytics dashboard reported a total failure for a new Microsoft Teams app launch: 1 visitor, 1 visit, 1 pageview. It looked like a complete flop.
But we dug into the raw logs (the upstream ground truth) and found a totally different reality: 159 events from 121 unique visitors, with a 31.4% share rate. The dashboard was hallucinating a 12,000% error.
It's a stark reminder: Don't trust the dashboard; trust the pipeline. If you're not observing your data at the source, you're flying blind.
Couldn't agree more! The shift to context-rich data for AI agents you hightlighted is a game-changer. So insightful.
The benchmarks comparng DuckDB, Polars, and Daft on 650GB are eye opening. DuckDB finishing in 16 minutes vs PySpark taking over an hour really shows how single node engines have evolved. Netflix's aproach to knowledge graphs and Uber's I/O observability work are also fasinating reads. Thanks for curating such valuable contnt every week.