Fixrecord

Fixrecord is a concept in data management describing a set of procedures and tools intended to repair or reconcile records in a dataset that are incorrect, inconsistent, or incomplete. It is commonly used within data cleaning and data quality workflows to improve the accuracy and reliability of stored information.

Typically, a fixrecord workflow begins with validation, where records failing predefined rules are flagged for correction. Depending on the context, a fix strategy may be fully automated, semi-automated, or manual. Automated strategies include rule-based substitutions, pattern matching, data type coercion, normalization, deduplication, and imputation of missing values. Semi-automated approaches may involve human review of proposed changes, with governance controls to ensure alignment with business rules. Changes are applied to the source data or a staging area, and an audit trail is created to document what was changed, when, and by whom. In some implementations, fixes are reversible and versioned to preserve provenance.

Common applications include customer data platforms, data warehouses, log and event data, and sensor or telemetry streams, where inconsistencies or format drift are frequent. Examples include standardizing date formats, harmonizing country or currency codes, correcting common misspellings, filling missing fields with derived values, and resolving conflicting fields through domain-specific rules.

Limitations and governance: automated fixes can propagate errors if rules are incorrect, so fixes should be tested and reversible, with clear business justification and impact assessment. Fixrecord is not a substitute for data quality design but a complement to validation, monitoring, and governance.

See also: data cleaning, data repair, data governance, record linkage.