Data Cleansing

For Error-free, Consistent and Usable Data

Irrespective of the data type, it is essential to maintain the quality of the

data. Inaccurate data with noises and impurities can severely impact the

insights and results coming out of it. Especially in the modern-day

scenario, where data from multiple sources are being used and blended

simultaneously to get insights, such data inconsistencies and issues are

inevitable. Hence, it is essential to clean the data so that error-free,

consistent, and usable data can be obtained. By means of data cleansing,

the corruptions within the data can be identified and corrected/ deleted.  


Various activities are needed to be done to ensure a smooth and seamless

Data cleansing process. For example, the errors need to be monitored to

see the pattern. This can make tracking much easier. Also, the data

cleansing process needs to be standardized and automated so that it can

deal with the huge volume of data coming from multiple data sources.

Proper validation of the data post cleansing is also essential to ensure that

no data is lost or manipulated by the process.