data observability

[hectorin]

Data observability is all about ensuring your data pipelines deliver correct, complete, and timely information. By tracking metrics like record counts, schema changes, and lineage, you catch issues before they snowball downstream. Modern platforms—Monte Carlo, Soda, and newcomers like Sifflet Data—auto-instrument pipelines and surface per-row diagnostics so you can pinpoint and fix errors fast