Why doesn’t the system detect spelling differences caused only by case variations?

• The data loading automation does not include spell-checking or case normalization features. While Resilinc automates the data validation and loading process, it checks for exact matches when identifying duplicates. 
  
  
• If two entries have the same spelling but different casing (for example, "ProductName" versus "productName"), the system will not recognize them as duplicates. 
  
  
• The automation validates data types, required fields, and business rules, but it does not normalize text case or perform fuzzy matching on similar spellings.

We can definitely implement case normalization and spell-check as part of the automation. However, we intentionally avoid modifying customer source data because each customer may have a specific intent behind how their data is entered (including casing, abbreviations, or terminology). Changing it automatically could lead to misinterpretation or loss of meaning.

Additionally:

1. Customers often rely on their original data format for internal consistency across systems, so altering it may create mismatches.
   
   
2. What may appear as a spelling inconsistency could actually be a valid business term, code, or naming convention.
3. Maintaining data in its raw, source form ensures traceability and auditability.