Data flows
Make the data arriving tomorrow trustworthy.
Zerg builds data pipelines with checks for the values your business depends on. It can use failed reconciliations, schema changes, and runtime errors to guide repairs.
What the work produces
Reconcile
Check counts, totals, and expected values
Recover
Test replay and backfill paths
Improve
Turn recurring failures into better checks
The problem
The details are where the work lives.
A job can finish successfully and still deliver the wrong data. Renamed columns, missing records, and changed business rules can affect decisions long before someone notices.
How we approach it
Build the checks into the work.
- 01
Define source and destination contracts, transformation rules, and checks for completeness, freshness, and valid values.
- 02
Build loaders, transformations, reconciliation checks, and bounded replay or backfill paths.
- 03
Use check results to investigate failures, repair the pipeline, and improve the tests for future runs.
Who it helps
Data and operations teams where missing, stale, or incorrect records have a real business cost.
The systems involved
Data flows