Data‑Quality handbook dropped

freeCodeCamp published a new “Data Quality Handbook” on April 14, laying out how engineers can stop bad data before it reaches production. (freecodecamp.org) The handbook was written by Great John and published on freeCodeCamp’s news site under its #data tag. It frames data quality as an engineering problem, not just an analyst or governance problem. (freecodecamp.org) Data quality is the basic question of whether a dataset is accurate, complete, valid, consistent, unique, timely, and fit for purpose. IBM lists those dimensions as the core checks organizations use to judge whether data can be trusted. (ibm.com, ibm.com) The handbook organizes those checks into validation layers: front end, back end, database, service logic, and jobs or ingestion pipelines. Its point is simple: each layer should catch a different class of error instead of assuming another system already did it. (freecodecamp.org) That approach mirrors the failures it uses as examples. The article cites Knight Capital’s August 2012 software error, which triggered unintended trades and cost the firm about $440 million in 45 minutes, and Target’s failed Canada expansion, where inaccurate product and inventory data contributed to losses of more than $2 billion before the chain shut its Canadian stores in 2015. (freecodecamp.org) The piece also uses the 1999 Mars Climate Orbiter loss to show how bad data can come from mismatched units, not just missing fields or typos. One team used metric units and another used imperial units, and the spacecraft was destroyed after entering the atmosphere at the wrong altitude. (freecodecamp.org) freeCodeCamp has been building out these longer handbook-style resources since launching freeCodeCamp Press in August 2023. The organization said then that it planned to publish more 5,000-word handbooks and full-length books on its community publication. (freecodecamp.org) The timing lines up with a wider push by companies to tighten how data is checked before it feeds dashboards, pricing systems, automation, and artificial intelligence tools. IBM said in a 2025 Institute for Business Value report that 43% of chief operations officers identified data quality issues as their most significant data priority. (ibm.com) The handbook closes with testing guidance that maps validation to unit, integration, and functional tests, so teams can check schemas, trace data through systems, and enforce business rules before release. It is free to read, which fits freeCodeCamp’s broader model of publishing developer education without a paywall. (freecodecamp.org, freecodecamp.org)