CSV Error Handling

CSV Error Handling

If there are any errors relating to the CSV file you are trying to upload, the application will inform you appropriately with an error message and explanation on top of your screen, as highlighted below:



The only file to which this does not apply is Stage_GL_Data, since that file is typically handled by the Monitor Service, due to its considerably larger size. Any specific issues with Stage_GL_Data will be reported in the "System Messages" tab when you expand Stage_GL_Data (along with a corresponding “CSV Upload Failed” status). The error messages you will receive will be similar in fashion to the error messages you receive via the web front end.


The following table explains commonly encountered errors with the files handled by the web front end.


Error Type



Invalid Data Type Error

[UPLOAD FAILED]: (fte_date.csv) Bad data was detected. See details below:

  • Sorry, but bad data was detected on row 18 column 7. Value given: FAIL HERE (Expected data type: int)



A data type is on a certain column that is not of the defined data type. (Example: "hello" appearing on a column that is of type int.)

Nullability Error


[UPLOAD FAILED]: (fte_data_null.csv) Bad data was detected. See details below:

  • Sorry, but a null value was detected on row 27 column 2 and the column was defined as not nullable.

A null value is provided on a certain column that is defined as not nullable.

Malformed CSV Error

[UPLOAD FAILED]: (fte_data_malformed.csv) Sorry, but the CSV file is not properly formed on row 20. This is usually caused by an unescaped double quote (") character or an invalid number of columns on the row. To fix this, please validate that any double quote characters within the data in the fte_data_malformed.csv is escaped by replacing the double quote (") with a single quote (') or validate that the number of columns is consistent across the CSV file. Then, please retry the upload.

A Malformed Error means that the application detected that a row of CSV data does not match the number of columns for its destination table. 

Scenarios which cause this include:

  • A row has a varchar column with a comma (,) in the value, but the column was not properly qualified with double quotes

  • Example: "Doe","John",Doe,John --> should be "Doe","John","Doe, John"

  • A row has a varchar column with a double quote (") in the value, but it was not replaced or escaped

  • Example: "Doe","John","Doe, John "Johnny"" -- fixes below

  • Option 1 (Escape the Double Quote): "Doe","John","Doe, John ""Johnny"""

  • Option 2 (Replace the Double Quote With a Single Quote): "Doe","John","Doe, John 'Johnny'"



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