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Krishna09
Helper III
Helper III

Date type errors - replace text values in datatype cellls

Hello,

I am creating a dataflow to import sharepoint file data to existing table in dataverse.

As I alredy defined data types in dataverse all column types should match. 

I have date columns in sharepoint excel file. where few row have text(Unclassified) but most of the cells date format is fine. Now with what type of value can I replace with Unclassified text in datetype column, so that it satisifies datetype?

Please guide me. 

1 ACCEPTED SOLUTION
AntrikshSharma
Community Champion
Community Champion

@Krishna09 Replace the value with null and then change the data type, I assume the column isn't going to be used in a relationship.

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4 REPLIES 4
Krishna09
Helper III
Helper III

@AntrikshSharma you are right Now the flow is runnning fine. 

I have one more table with almost same data types. I created a data flow to import data of csv file from sharepoint to existing table in dataverse. only 56 row were imported and I received an error. 

It says dataa source credientials are invalid. if it is so, how could it import 56 rows?.

how to solve this error?

Error message:-

The dataflow could not be refreshed because there was a problem with the data sources credentials or configuration. Please update the connection credentials and configuration and try again. Data sources: Schema evaluation did not return TableResult. Actual result type: Challenge, Bad credentials, Challenge type: Resource, DataSources:

Krishna09_0-1667573419981.png

 

Krishna09
Helper III
Helper III

@AntrikshSharma I replaced with null value. later when I publish, no data was imported to dataverse. Besides, I received an error. I tried to refresh twice. All the time I refresh , same error pops up.

Why this error?

how to rectify this error?

Krishna09_0-1667568271011.png

 

@Krishna09 Maybe there are some other values in the column that are text, try to run a Distinct over that column.

AntrikshSharma
Community Champion
Community Champion

@Krishna09 Replace the value with null and then change the data type, I assume the column isn't going to be used in a relationship.

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