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Alteryx Analytics allows users to organize, clean, and analyze data in a repeatable workflow. Business analysts find this tool particularly useful for connecting to and cleansing data from data warehouses, cloud applications, spreadsheets and other sources.
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RegEx has a One Tool Example. Visit Sample Workflowsto learn how to access this and many other examples directly in Alteryx Designer. Use RegEx (Regular Expression) to leverage regular expression syntax to parse, match, or replace data.
Alteryx uses the ISO format yyyy-mm-dd HH:MM:SS to represent dates and times. If a DateTime value is not in this format, Alteryx reads it as a string. To convert a column for use and manipulation in the DateTime format, use the DateTimeParse function in the expression editor or the DateTime Tool.
The above phrase [^A-Za-z] is basically telling Alteryx to replace anything that isn’t upper or lower a to z. We didn’t specify any of the special characters including a space. Lets try adding a space. The formula now looks like this [^A-Za-z\s] The next is to add the other special characters , ( ) &. The new formula would be [^A-Za-z\s, ()&]