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Data Science - Interview Questions
What is the importance of Data Cleansing?
As the name suggests, data cleansing is a process of removing or updating the information that is incorrect, incomplete, duplicated, irrelevant, or formatted improperly. It is very important to improve the quality of data and hence the accuracy and productivity of the processes and organisation as a whole.
 
Real-world data is often captured in formats which have hygiene issues. There are sometimes errors due to various reasons which make the data inconsistent and sometimes only some features of the data. Hence data cleansing is done to filter the usable data from the raw data, otherwise many systems consuming the data will produce erroneous results.
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