Data quality, especially data cleaning, is surveyed in this paper. The importance of data quality, and its measurement metrics are described. The data cleaning problems are defined and classified. The approaches to solving data quality problems are detailed. How to combine the techniques in other research areas with data cleaning is overviewed, and several data cleaning frameworks proposed previously by others are introduced. The future research topics related to data cleaning problems are also discussed.