摘要
Abstract
This paper firstly introduces the basic concepts and objectives of data cleaning and preprocessing and their importance in data analysis.Then,it analyzes the main challenges of data cleansing in the big data environment,including the data volume challenge brought by handling large-scale data sets,the quality problem of multi-source data,and the limitations of existing techniques and tools.In addition,this paper explores several improved data cleansing and preprocessing approaches,especially machine learning-based data cleansing techniques and efficient data preprocessing strategies to cope with the specific needs of big data.Finally,the article summarizes the important role of data cleansing and preprocessing techniques in big data analytics and provides an outlook on the future direction of development.关键词
大数据/数据清洗/数据预处理/机器学习/数据分析Key words
big data/data cleaning/data preprocessing/machine learning/data analysis分类
信息技术与安全科学
