If your data is in Excel and has blank rows, Dataverse will still read these records but populate the values with NULL.
For example, my data in Excel looks like the following - as you can see, rows 4, 10 and 11 are blank:
When I read this worksheet into Dataverse, the data looks like this:
You can see above that the blank lines have been populated with NULL.
Remove blank rows
In many cases, these blank lines offer no additional value and it's best that we exclude these rows.
Using where statement
If we have already read our data, we can easily remove the NULL records by using the where clause.
For example, in a Transform node, you can use the following Dataverse script:
emit * where 'id'.isNotNull()
You may prefer to use 'id'.isNotNull() as the predicate in the Split node if you want to have visibility of the records that you are removing.
Using Excel File property
You can actually ignore the blank rows at the time the data is read in. In the Excel File node, set the 'NullRowAction' property to be "Ignore" and blank rows will not be read into Dataverse: