1. A method of processing vehicle driving data by a big data processing apparatus, the method comprising: detecting a first outlier in each field of sensing data included in the vehicle driving data, the first outlier representing field values out of a predetermined range; generating first refined data by correcting or removing the first outlier from the sensing data; detecting a second outlier in the first refined data, the second outlier representing field values having a deviation greater than a predetermined threshold between consecutive field values of a same field or between different fields correlated to each other; and generating second refined data by removing the second outlier from the first refined data; generating statistical data based on the second refined data; and performing mining analysis based on at least one of the second refined data and the statistical data.