Ab Initio Data Quality New! 【PLUS】

Go ab initio , or go home. [Your Name] writes about the intersection of rigorous engineering and practical data science. Disagree with the zero-NULL policy? [Link to comments or Twitter.]

You enforce quality at the point of creation or ingestion. If a record doesn’t meet the first principles of your domain (e.g., timestamp cannot be in the future; customer_id must match a regex), it is rejected immediately. The rule: Do not allow a known violation to enter your persistent storage. Ever. 2. The "Nullable Integer" Paradox Let’s look at a classic first-principles failure: Nulls in numeric fields. ab initio data quality

Replace NULL with explicit semantics. Use -999 for "offline," -9999 for "out of range," or better—split the column into value and value_metadata_flag . 3. The Referential Integrity Illusion Modern data lakes love "schema on read." This is the enemy of ab initio . You are essentially saying, “Let’s store the garbage, and we’ll figure out what kind of garbage it is later.” Go ab initio , or go home