As far as I know, when we deal with 'big data'. It is common we deal with more than 10 years' customers data. Quality issue is always there. What I am thinking about, to what extend we should deal with the data quality issues? A robust algorithm should tolerate with the data quality issues but if we do better data cleansing work we get outcome confidently.So how to balance this? Somebody please give some ideas!Thanks. 
About data cleansing, to what extent should we do our work?
data cleaning;data