The choice of data cleaning software depends on various factors:
Complexity of Data: For large and complex datasets, more advanced tools like SAS or Trifacta may be more suitable. User Expertise: Tools like OpenRefine are user-friendly, while Python and R require programming knowledge. Cost: Some tools are free (e.g., Python libraries, R packages), while others may be costly. Integration: The software should integrate well with other tools used in your workflow.
