Most data quality systems don’t die of bad checks. They die of a missing field in the rule model: the severity. A missing country code in three out of 80,000 rows blocks the nightly load, someone switches the check off “temporarily”, and from that moment everything runs unchecked. Steering data quality with severity levels instead of binary … Read more
The rule “country_code is mandatory” lives in your database twice: once as NOT NULL in the target table’s schema, and once as a hand-typed row in the check configuration. On the next ALTER TABLE, only one of the two places changes, and the check silently goes wrong. With derived data quality rules you no longer type that repetition: the metadata already … Read more
Bad data gives no warning. An age of 200 years, a duplicate customer number, a country code that doesn’t exist — in the source system nobody notices. Only when the ETL run tries to push the rows into the strictly modelled target layer does the load break: on a CHECK, on a UNIQUE index, on a foreign key. Checking … Read more
“We do ETL.” You hear it in almost every data team — and it is often wrong. If every transformation runs as a stored procedure after the raw data has already been loaded, unchanged, into a staging table, then what you have is really ELT. The label hides what is actually happening. The difference between ETL vs. ELT is … Read more
A single date string that cannot be parsed, and the entire ETL run aborts. The design pattern for ETL process architecture presented here prevents exactly that: bad data is isolated, not passed along. TL;DR — what this article covers: Prerequisite. Basic familiarity with ETL processes. This is a conceptual article — not a step-by-step tutorial. Root of … Read more
A single value that cannot be converted — a date in the wrong format, a number with the wrong decimal separator — and the entire ETL run aborts. Data quality in an ETL process means catching such errors proactively: identifying, logging and isolating them before they reach the target system. This article is the entry point to … Read more
An ETL process finishes without an exception — but was everything really loaded that should have been? The mere fact that a process did not abort says nothing about whether it actually did what was expected of it. A readable, evaluable log is what turns a gut feeling into a defensible statement. This design pattern … Read more
