Data truncation

Data truncation happens when a database attempts to store data that is larger than the size allocated by the database schema. For example, inserting a 50-character string into a SQL column defined to store only 20 characters results in truncation of the remaining characters. This leads to incomplete or corrupted data, which can cause logic errors, incorrect processing, or loss of important information. Data truncation often indicates a mismatch between application expectations and database design, pointing toward issues with schema definitions or input validation.

To fix data truncation errors, first ensure that your database schema accurately reflects the size and type of data expected by your application. Increase the column size or alter the schema appropriately if longer data entries are required. Implement strict data validation in your application layer to ensure input data fits the defined constraints before insertion. Use database constraints, validation logic, or stored procedures in SQL databases to enforce these rules consistently. Additionally, monitor logs and perform regular schema audits to identify and proactively address potential truncation issues before they lead to data loss.