A data analyst attempts to import a daily orders.csv file into a database table. The import process fails, citing a 'data type mismatch' error on a specific row. Upon opening the file in a plain text editor, the analyst observes that a comma was used within the product_description field on that row, but the entire field was not enclosed in double quotes. This has caused all subsequent data for that row to be shifted, misaligning values with their intended columns. Which of the following is the most likely cause of this data corruption?
The network transfer of the file was interrupted, causing a truncated file.
The source file contains improperly escaped delimiters.
There is a character encoding mismatch between the source file and the database.
The target table's schema has incorrect data types for the columns.
The correct answer is that the source file contains improperly escaped delimiters. In a comma-separated values (CSV) file, the comma acts as a delimiter to separate columns. If a comma is part of the data within a field (like in the product_description), the entire field must be enclosed in a text qualifier, typically double quotes, to signal to the parser that the comma is not a delimiter. When this rule is not followed, the parser incorrectly interprets the comma as the end of the field, causing all subsequent values in that row to be shifted to the next column, leading to data type mismatch errors.
A character encoding mismatch typically manifests as garbled or incorrectly displayed characters (mojibake), not a structural shift of columns.
An interrupted network transfer would more likely result in a truncated or incomplete file, which might cause an 'unexpected end of file' error, rather than a clean column shift on an intact row.
While the final error is a data type mismatch, the root cause is not the target table's schema. The analyst's investigation confirmed the data itself was malformed in the source file, which then failed to align with the (presumably correct) schema of the destination table.
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