DATA OPS
BigQuery value-shape drift sentinel for unmodeled JSON columns
Profiles the JSON value shapes inside semi-structured BigQuery columns on a schedule, detects when new keys appear or a field's value type shifts.
How it runs
The automated pipeline, trigger to output.
- TriggerProfiling schedule fires
- ActionSample recent rows of semi-structured columns in BigQueryBigQuery
- LogicInfer nested key set and per-field value types
- LogicDiff inferred shape vs stored profile; stop if unchanged
- OutputPost value-shape drift to Discord analytics channelDiscord
What it does
Many warehouse columns hold raw JSON whose declared type is just `STRING` or `JSON`, so a normal column-type check never catches changes inside them. This workflow samples recent rows of those semi-structured columns, infers the key set and value type of each nested field, and compares the inferred shape to the last profile. New keys, disappeared keys, or a field flipping from number to string get flagged and sent to Discord.
When to use it
Use it on event or payload tables where upstream producers change their JSON contract without touching the warehouse column definition, the kind of drift that quietly corrupts extraction logic downstream.
How it works
- 1A schedule triggers the profiling run.
- 2Sample recent rows of the tracked semi-structured BigQuery columns.
- 3Infer the nested key set and per-field value types for the sample.
- 4Diff the inferred shape against the stored profile to find new, missing, or retyped fields.
- 5If the shape is unchanged, save the profile and stop.
- 6Post the value-shape drift to the analytics Discord channel and persist the new profile.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect DiscordCommunity channels + voice + bots.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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