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In step three of the data analysis process, the data collected is processed and verified. Raw data must be converted into a usable format and this often requires parsing, transforming, and encoding. This is a good time to look for data errors, missing data, or extreme outliers. Basic statistical summary reports and charts can help reveal any serious issues or gaps in the data. How to fix the issues will depend on the type of problem and will likely need to be considered case-by-case, at least at first. Over time, company protocols may be developed for specific data issues. Especially in a new data science solution, the data almost always needs a little repair work.