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.