Data maintenance
The ongoing work of keeping stored data accurate, current and consistent across its lifecycle, including correction, review of its classification, and removal of stale copies.
Data maintenance is the lifecycle stage between collecting data and disposing of it, while the data is held and used. It covers correcting errors, updating records that have gone out of date, reconciling duplicate copies, confirming that backups and replicas still match the source, and checking periodically that the data classification applied at creation still fits. For personal data, GDPR Article 5(1)(d) gives part of this a legal footing: personal data must be accurate and, where necessary, kept up to date.
Within the data lifecycle, maintenance is distinct from data retention, which decides how long data is kept, and from data quality, the property that maintenance sets out to protect. The roles divide in the usual way: the data owner sets the requirements, a data steward commonly looks after accuracy and meaning, and the data custodian runs the technical work such as backups and integrity checks. Neglected maintenance tends to surface as security risk: forgotten copies, records carrying the wrong label, and data kept long after its purpose has ended.
Exam relevance: data maintenance appears by name under objective 2.4 of the ISC2 outline. A scenario is likely to describe stale, duplicated or inaccurate data and ask which lifecycle activity or which role should deal with it. Candidates are expected to keep maintenance separate from retention and destruction.