How do you keep large datasets accurate and free from duplicate records?

[jamesfredwick]

Keeping data accurate can become difficult when information is collected from multiple sources. Duplicate entries, inconsistent formats, missing fields, and outdated records can gradually reduce the quality of a dataset and make everyday tasks more time-consuming.

I’ve been exploring data cleansing services as a way to improve the quality of existing records without relying entirely on manual checks. A proper cleansing process can help identify duplicate information, correct inconsistencies, standardize records, and remove unnecessary or outdated data.

This seems particularly useful for teams that regularly work with customer, contact, sales, or operational records. Having cleaner data can make reporting easier and help teams work with more consistent information across different systems.

For those managing large datasets, what approach has worked best for you? Do you prefer handling data cleanup manually, using spreadsheets and scripts, or relying on automated data cleansing solutions?