What are Salesforce best practices for maintaining data quality over time?

Data quality decays unless something actively maintains it, so I design for the ongoing state rather than a one-off cleanse:

1. Prevent at entry: Required fields where genuinely required, validation rules, picklists instead of free text for anything that will be reported on, and Duplicate Management with matching rules tuned and duplicate rules set to block or alert on the entry points that matter — including the API, which is often left unchecked.
2. Standardise: Address normalisation, consistent formats for phone and identifiers, and a single source for reference data rather than each integration inventing its own values.
3. Measure: Define quality metrics per domain — completeness on key fields, duplicate rate, staleness — and report on them on a dashboard that someone actually owns. Unmeasured quality is unmanaged quality.
4. Assign ownership: Named data owners per domain and stewards with time allocated to work exception queues. This is the control most often missing.
5. Govern change: Change control on the data model so fields are not added ad hoc, plus periodic field-usage review to retire fields nobody populates.
6. Remediate in cycles: Scheduled deduplication and enrichment runs rather than an annual heroic cleanup project.