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Once your list is configured to display those fields, you can narrow down your results by a filter if necessary. From here you can make whatever changes you want in the spreadsheet itself.We could even change the names and contact information for our People, and because we’re using the ID number, Pipedrive will force the update to go through to that specific record, even if the names don’t match.

We could use the bulk editing and filtering abilities of our list views to edit data in large chunks, but what if you already have all the data you need in a spreadsheet, and you just need to get it into Pipedrive without creating duplicates?

The rowset size to be used by SQLBulk Operations is set by a call to SQLSet Stmt Attr with an argument of SQL_ATTR_ROW_ARRAY_SIZE.

Unlike SQLSet Pos, which uses a new rowset size only after a call to SQLFetch or SQLFetch Scroll, SQLBulk Operations uses the new rowset size after the call to SQLSet Stmt Attr.

To update information in bulk, we can download a list of our currently existing data — which includes the ID fields — make the necessary changes in our spreadsheet, and then upload that spreadsheet to Pipedrive using the ID field to easily map the new data to our records.

These ID numbers can be found in the URL of your record, or in the list views.

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