With out changing any dat type----error:- OLE DB or ODBC error: Type mismatch.

[Krishna09]

Hi All,

datasource is hsarepoint. A power BI was already connected to to sharepoint. I have downloaded it and made required changes to it. But, I have not changed any datatype. 

When i got to apply the changes ive made in the EDIT QUERIES, the message: "OLE DB or ODBC error: Type mismatch. (Exception from HRESULT: 0x80020005 (DISP_E_TYPEMISMATCH))" comes up.

Failed trails:- 1.  from many suggestions in online,  I have changed datatype. It didnot work.

                      2. checked if there is any dataa type change happened. But no data type is changed.

[Finbar31]

I might be able to help. If your field types are correct, then maybe look at any calculated fields or measures within the visuals. I found that even if it could load the data and process the fields, it would still error. I tracked it down to an "n/a" in an ABC123 field. The field type wasn't a problem but I followed it up with a calculation in the visuals - this is why it errored at the end of the loading sequence.

[Krishna09]

@MAwwad Thank you very much. I tried the steps you suggested. they didnot work. Later I created new one. It worked.

[Krishna09]

@MAwwad Thank you very much for your response . I have tried your suggestion. None of them worked. So I created a new one and published. It worked. 🙂

[MAwwad · Accepted solution]

The "Type mismatch" error usually occurs when there is a problem with the data types of the columns in the query.

Here are a few things you can try to troubleshoot the issue:

1. Check the data types of the columns in the query. Make sure that the data types are consistent with the data in the source. For example, if a column contains numeric data, make sure that the data type is set to "Whole Number" or "Decimal Number" in the Query Editor.

2. Check for any errors in the data. Make sure that all values in the columns are of the correct data type. For example, if a column is set to the "Date" data type, make sure that all values in the column are valid dates.

3. Check for any formatting issues in the data. Make sure that all values in the columns are properly formatted according to the data type. For example, if a column is set to the "Currency" data type, make sure that all values in the column are formatted as currency.

4. Check for any missing or blank values in the data. Make sure that all required columns have values, and that all values are properly formatted according to the data type.