Production-scale Canada B2B data automation.
A data and automation platform built to consolidate, normalize and serve nationwide Canadian business-establishment data while preserving provenance, operational controls and repeatable validation.
From fragmented records to an operational B2B dataset.
The completed production checkpoint contains more than 2.7 million live establishments and covers all 10 Canadian provinces and 3 territories. The system was designed around repeatable ingestion, normalization, provenance and regression safety rather than a one-off spreadsheet export.
2.7M+ live establishments
Production data reached 2,743,454 live establishment records at the completed scale-import checkpoint.
815K+ organizations
Organization-level records reached 815,427, with establishment and parent-organization relationships supported in the production data model.
Nationwide coverage
Coverage spans Canada's 10 provinces and 3 territories, allowing the platform to support nationwide B2B discovery and analysis.
Built for repeatable data operations.
The implementation combined database engineering, import automation, validation and operational monitoring so large datasets could be processed without sacrificing traceability.
Structured ingestion
Large source datasets are transformed into normalized establishment and organization records with controlled import behavior and regression checks.
Data provenance
Provenance is retained so records can be traced to their source and the system can distinguish verified source data from inferred or unsupported attributes.
Durable processing
A persistent worker and scheduler support repeatable background processing while health checks verify the database, API and application surfaces.
Production safeguards
Scale work was validated against database health, schema state, dashboard behavior, new-business handling, CSV regression and unintended-write checks before release evidence was accepted.
Scale only counts when the system still works.
The final release checkpoint used PostgreSQL 16 with schema version 0005 and API version 0.2.0. The verified test run collected 435 tests: 423 passed, 12 were skipped and none failed. Fresh-image migration from schema 0001 through 0005 was also verified in a disposable database.
This case study intentionally reports implementation evidence rather than invented revenue, conversion or client-outcome claims.
Automation can extend far beyond workflow builders.
The Canada B2B project demonstrates LukeZigger's broader delivery model: understand the operational requirement, choose the right architecture, engineer the system, validate it at production scale and keep the result maintainable. The same approach can be applied to data operations, reporting, research systems, CRM enrichment, back-office processing and custom business automation.