Abstract

With the rise of the big data technology storm in the computer field, the scale effect of big data computing has also brought great challenges to the storage, processing, management and visual analysis of computer data, and different data types, so the data will be mixed with incomplete, repeated or even wrong "dirty data". The direct output of these 'dirty data' will seriously affect the accuracy and efficiency of data decision-making. It can lead to incomprehensible results. Therefore, data cleaning of raw data is a key link in the process of big data analysis and application. This article elaborates on the overview and classification of data quality, the principle and basic process of data cleaning, and the methods of data cleaning [1].

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