What are the best methods for data cleaning?
Create a data cleaning plan by understanding where the common errors take place and keep all the communications open.
Before working with the data, identify and remove the duplicates. This will lead to an easy and effective data analysis process.
Focus on the accuracy of the data. Set cross-field validation, maintain the value types of data, and provide mandatory constraints.
Normalize the data at the entry point so that it is less chaotic. You will be able to ensure that all information is standardized, leading to fewer errors on entry.
