Data analyst Q&A 11. What are the best practices for data cleaning?

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11. What are the best practices for data cleaning? If you are sitting for a data analyst job, this is one of the most frequently asked data analyst interview questions. Data cleansing primarily refers to the process of detecting and removing errors and inconsistencies from the data to improve data quality. The sample answer is… 1. Make a data cleaning plan by understanding where the common error take place and keep communication open 2. Identity and remove duplicates values before working with the data. This will lead to an effective data analysis process 3. Focus on the accuracy of the data. Maintain the value types of data, provide a mandatory constraints and set cross-field validation. 4. Standardize the data at the point of entry so that it is less chaotic and you will be able to ensure that all information is standardized, leading to fewer errors on entry.