If you’re working in Wdata and building out your first table, you may be wondering what all of the column types are and why they’re important. If so, this is the right community post for you! Column types specify the structure of data that is saved in the column. Having the correct column type is important because it helps with data validation and potential aggregation down the line. 

You can manage column types from the beginning of table creation and after the table has been created. If you are editing an existing table, you will need to make sure that the datasets are staged in the table when making edits to columns. Once you’re done making edits, be sure to import the datasets again. 

The guidelines below are important to follow because column types drive your ability to perform certain actions within queries. For example - any integer or decimal fields will be automatically summed in query creation. You can alter the calculations in the query to give you exactly what you need. Calculations in queries rely on the column type being either integer or decimal. These guidelines are also important because they ensure that the values being imported match the structure of the column. For example - if a string of characters other than an integer is imported to a column with the integer column type, you will get an error message during import because the value doesn’t fit within the column.

The column types available in a table and the structure of their values are:

Once you have the appropriate column type selected, you will want to check the import format. This is specifically important for date and timestamp column formats. Make sure the import format matches the format of the date in the file you are importing. 

You may want to consider creating any Year, Quarter, Reporting Period, Account Number columns, etc. as a Text field. These fields are generally whole numbers, but those numbers will not be increased, decreased, or aggregated. Therefore, for validation purposes, you can create them as a text field to ensure they are not altered. For example, Wdata queries will sum integer and decimal fields by default, so switching year, quarter, reporting period and account number columns to an integer will help ensure those fields are not summed. 

These column type guidelines stand true for other areas of the data management suite as well! It’s recommended to use these guidelines for column types in Data Prep Pipelines and Sample Files. 

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