Now a day’s big data science is the easiest way for industries to collect their data in an organized manner with descriptive statistics. But big data is not 100% accurate and can’t match data in different formats allowing the duplication of data and retarding the quality of data thereby. So how can we improve the quality of our data?
We should have a proper data model initially to store our data and continue further with that data. We should then compare the data from end to end and clean the data by merging the recurrent data and removing corrupted and unnecessary information. Apart from cleaning the existing data, we should also be care full while collecting the data and entering it into a data model. Because not all the data is authorized and safe. We should be cautious while transferring our data from a data lake to a data warehouse. We should also check the information regularly for its performance.
