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Data Quality

11
Aug
A grayscale close-up of a precision measurement compass in sharp detail, representing the quality thresholds that data platforms run on when they are defined rather than inherited.

Data quality is not an engineering problem

Most data quality problems are not engineering failures. They are quality decisions nobody made — thresholds inherited by default, definitions that were never agreed, policies that exist only as institutional habit.
4 min read
16
Jun
A glowing amber dial on a dark dashboard reads 93% Quality, surrounded by blurred gauges, representing a confident metric that does not confirm the data itself is correct.

Your dashboards are green. That does not mean your data is correct.

Data observability tells you when something broke, but it does not tell you whether the data was ever correct. Confusing the two is one of the most common sources of false confidence in a data platform.
4 min read