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It goes without saying that data is the cornerstone of any data analysis.
As for data, there are millions of things that can be faulty. It can be the arrangement, additional spaces, data format problems, duplicates – the list goes on.
Before you know it, data analysis can become your personal nightmare. Just think about it: data specialists spend up to 80% of their time organizing and cleansing data, whereas the other 20% is allocated to data analysis itself.
It’s quite a counter-effective ratio, isn’t it?
(There exists an alternative joke: Data scientists spend up to 80% of their time organizing and cleaning data and 20% of their time – whining about it. We feel you. Data cleanup is like beating the wind.)
As you can see, proper data analytics calls for various data cleansing techniques so that your data is all set for analysis.