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Jul 19, 2006 · main solution approaches. Data cleaning is especially required when integrating heterogeneous data sources and should be addressed together with schema-related data transformations. In data warehouses, data cleaning is a major part of the so-called ETL process. We also discuss current tool support for data cleaning. Shapiro, 2008] lists a number of current commercial data cleaning tools.) The space of tech-niques and products can be categorized fairly neatly by the types of data that they target. Here we provide a brief overview of data cleaning techniques, broken down by data type. Quantitative data are integers or oating point numbers that measure ... Data cleaning is a crucial part of data analysis, particularly when you collect your own quantitative data. After you collect the data, you must enter it into a computer program such as SAS, SPSS, or Excel. During this process, whether it is done by hand or a computer scanner does it, there will be errors.