{
  "id": "dwd_gxekubnp",
  "type": "term",
  "slug": "data-quality",
  "title": "Data quality",
  "summary": "Rules data must satisfy, and the measured results of checking it against them.",
  "status": "draft",
  "classification": "public",
  "authors": [
    {
      "name": "Shan Umasankar",
      "url": "https://dealwithdata.com",
      "role": "author"
    }
  ],
  "assisted_by": [
    "Claude"
  ],
  "scales": [
    "personal",
    "business",
    "enterprise"
  ],
  "synonyms": [
    "DQ"
  ],
  "related": [
    "dwd_wg5zzqg2"
  ],
  "created": "2026-10-07",
  "updated": "2026-10-07",
  "version": 1,
  "url": "https://dealwithdata.com/glossary/data-quality/",
  "markdown_url": "https://dealwithdata.com/glossary/data-quality.md",
  "body_markdown": "Data quality is the gap between what data should be and what it is. Rules (\"never negative\", \"not null\", \"matches the reference list\") are checked, scored and monitored. Active data quality blocks or flags bad data *before* it reaches a critical report.\n\n**Example:** \"Outstanding balance must be \u2265 0 and not null\": 99.7% pass this run.\n\n**Not to be confused with** [[data-profiling]], which only describes.\n"
}