The term "data maintenance" refers to the continuous updating, correction, enhancement, and consolidation of data records within software systems. The objective of data maintenance is to ensure long-term data quality, avoid duplicate or incorrect entries, and provide a reliable information base for business processes and analysis. Data maintenance is a key component of data management and applies to both structured data (e.g., customer data, product information) and unstructured data (e.g., documents).
Duplicate Detection and Merging: Identifying and merging duplicate records (e.g., duplicate customer or article numbers).
Validation and Plausibility Checks: Automatically verifying data formats, required fields, and value ranges.
Auto-Completion: Completing missing data using rules, templates, or external data sources.
Versioning and Change Logging: Documenting data changes for traceability and quality assurance.
Bulk Data Editing: Simultaneous updating or correcting of large datasets (e.g., via import or batch functions).
Approval Workflows: Ensuring that changes are made only by authorized personnel through controlled approval processes.
Spelling and Format Corrections: Standardizing spellings and enforcing company-wide formatting guidelines.
Integration of External Data Sources: Matching and enriching internal data with external information (e.g., address directories, industry data).
A trading company removes duplicate supplier entries in its ERP system.
A sales representative updates outdated email addresses in the CRM system.
A data steward imports missing revenue figures from an accounting tool.
A company regularly checks the formatting of phone numbers to maintain a consistent standard.
A marketing team uses an approval workflow to validate new product descriptions in the product database.
