Null Handling Conventions for Customer-Facing Exports
Null values demand explicit contracts between systems or silent data corruption will follow.
Grain, additivity, and fact type prevent silent SaaS analytics failures.
Null values demand explicit contracts between systems or silent data corruption will follow.
Labeling what columns actually mean unlocks schema matching, data cleaning, and discovery.
How different data warehouses encode booleans and enums from PostgreSQL sources.
Cloud warehouses declare foreign keys for optimizer hints, not enforcement.
Breaking schema changes to exported tables risk cascading failures across dependent systems.
Inconsistent column names break silently across warehouses during migrations.
Define the three temporal columns that transform raw exports into analysis-ready datasets.
One WAL setting unlocks change data capture from Postgres to any downstream system.