{"product_id":"ai-data-governance-quality-management-system","title":"AI Data Governance \u0026 Quality Management System","description":"\u003cp\u003e\u003cem\u003eAn editable system for governing the data behind AI: where each dataset came from, whether it is fit for purpose, and the evidence that proves it.\u003c\/em\u003e\u003c\/p\u003e\n\u003ch2\u003eOverview\u003c\/h2\u003e\n\u003cp\u003eA model is only as defensible as the data it learned from. When a regulator, customer or auditor asks how a model was trained, the answer has to be a record, not a recollection. This system builds that record, one dataset at a time.\u003c\/p\u003e\n\u003cp\u003eIt lets you identify AI datasets, assign owners and stewards, document sources, provenance and lineage, set and assess data quality requirements, and record a fitness-for-purpose decision. Training, validation, test, synthetic and third-party data each have their own controls. The centrepiece is a dataset evidence pack, assembled for each significant dataset, that runs from the dataset profile to an evidence index.\u003c\/p\u003e\n\u003cp\u003eData quality management is built on ISO\/IEC 5259-3:2024. An AI data control framework is cross-referenced to ISO\/IEC 38505 on the governance of data and to ISO\/IEC 42001:2023. Standards are referenced by number and clause title only, and no standard text is included. The toolkit draws no legal conclusions, for example on data licensing, and leaves those to your legal advisers.\u003c\/p\u003e\n\u003ch2\u003eWhat this system covers\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eGovernance structure:\u003c\/strong\u003e a data governance framework, committee terms of reference, decision authority, data owner and data steward registers, and RACI.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eLifecycle policies and procedures:\u003c\/strong\u003e acquisition, provenance and lineage, preparation and transformation, labelling, synthetic data, version and change control, third-party data, retention and disposal, quality incidents and evidence.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eDataset control:\u003c\/strong\u003e inventory, classification and requirements, with a fitness-for-purpose method and records for acceptance, conditional acceptance and rejection.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eData quality:\u003c\/strong\u003e an organisation-level quality management plan, a quality characteristics matrix, a quality assessment workbook and a quality risk register.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTraining, validation and test data:\u003c\/strong\u003e management plans, registers and approval forms, plus tools for labelling, synthetic data and third-party datasets.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEvidence and assurance:\u003c\/strong\u003e the dataset evidence pack template with instructions, self-assessment, maturity and gap assessment, mock audit, corrective action, management review and a 90-day implementation plan.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho it's for\u003c\/h2\u003e\n\u003cp\u003eOrganisations that build or train machine-learning models on their own or third-party data, where dataset evidence matters most. The implementation owner is a chief data officer or data governance lead. Data owners, stewards, engineers and scientists use the registers and forms. Governing bodies, quality and AI assurance professionals, procurement, legal, risk and internal auditors each have a defined role.\u003c\/p\u003e\n\u003cp\u003ePrivacy is deliberately out of scope here and is covered by the AI Privacy Management System.\u003c\/p\u003e","brand":"Apex Global Solutions AGS","offers":[{"title":"Default Title","offer_id":57395131777364,"sku":"AGS-21-007","price":790.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1052\/4996\/4372\/files\/AGS-21-007.png?v=1790973830","url":"https:\/\/agskits.com\/products\/ai-data-governance-quality-management-system","provider":"Apex Global Solutions","version":"1.0","type":"link"}