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Hi,
Hope am reaching out to the right corner of Dynamics 365.
Below is the issue encountered while loading data using Azure Data Factory:
To extract the data from Dynamics 365 source using Azure Data Factory, we are using XML query in ADF which defines only specific set of columns to be pulled from the source. However, it has been noticed that though we define the column names(attribute names), few columns are missing out after the data is loaded into Data Lake file(.csv).
Here is an example for better clarification: Below is the XML query which has 9 columns but only 7 columns are getting extracted, upon checking the data we see the missing columns has large no. of NULL/ALL NULL values in the source. Kindly, please advice if there is any feasible solution to handle such scenarios.
<fetch version="1.0" output-format="xml-platform" mapping="logical" distinct="false">
<entity name="xts_employee">
<attribute name="createddate" />
<attribute name="modifieddate" />
<attribute name="xts_employeeid" />
<attribute name="xts_businessunitid" />
<attribute name="xts_employeetype" />
<attribute name="xts_status" />
<attribute name="xts_employeeregion" />
<attribute name="xts_joindate" />
<attribute name="xts_resigndate" />
</entity>
</fetch>
Thanks & Regards,
Pramod.
Hi Partner,
If the column data is null which means sparse, columns without any value in top rows would be missing. we suggest that you could use explicit column mapping.
I also find this thread about the same issue for you.
https://github.com/MicrosoftDocs/azure-docs/issues/21216
Regards,
Leo
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