Data cleaning for CRM imports

Dynamics 365 import errors

Fix "The source data is not in the required format" in a Dynamics 365 import

Dynamics rejects a value because its format does not match what the field or your org's locale expects. Almost always it is dates and numbers: a date read against the wrong locale, or a number with the wrong decimal separator, thousands commas, or a currency symbol. The fix is to standardize dates and numbers to a format your org accepts, before you import, not one rejected row at a time after.

Standardize your file in Sift, free →

What the error looks like

The message is generic on purpose: Dynamics tells you a value is in the wrong format, but not which cell. That is why the fix is to clean the whole column, not hunt one row.

Why it happens

• Date order, dd/mm vs mm/dd. Your file is one order and the org's locale and format settings expect the other, so a value like 07/05/2026 is ambiguous or lands on the wrong day.
• Decimal separator, comma vs dot. A number written 1.234,56 will not parse where a dot decimal is expected, and the reverse fails too.
• Thousands separators. A comma in 1,234 is a grouping separator to a person but noise to a number field.
• Currency symbols in a number column. A leading currency symbol or code makes the value non-numeric.
• A stray non-numeric character. A note, a footnote marker, or a space inside a numeric field is enough to fail the whole value.

The manual fix

1. Open your Dynamics personal options and note the locale, the date format, and the number format the org expects.
2. Match your file's date format to that locale, so a value like 07/05/2026 is read as the day you mean.
3. Remove thousands separators and currency symbols from every number column.
4. Use one decimal separator across the file, the one your org's locale expects.
5. Re-check the columns Dynamics flagged, then re-run the import.

The Sift fix

1. Drop your CSV or Excel file into Sift. It runs in your browser; the file is never uploaded.
2. Sift standardizes dates to an unambiguous format and previews the rows where the order was ambiguous, so you confirm 07/05/2026 means the day you intend.
3. Sift strips thousands separators and currency cruft from number columns, so 1.234,56 and 1,234 parse cleanly as numbers.
4. Review every change with a diff, then export the cleaned file and import it into Dynamics.

What Sift can't fix

Honesty matters here: Sift formats the file, but "the required format" also depends on each user's Dynamics personal options and the field definition, which Sift cannot read. So confirm your org's locale and date and number formats, and map the standardized columns to the right fields. And a value that is genuinely the wrong kind of data for the field, a note where a number belongs, still needs a human to decide what it should be.

Related guides