Use the Database matching validation to ensure that data extracted for a field matches entries in a column in your database. If the entries do not match, the file will be flagged for review.
Eg: Flag a file if invoice_number 12324 is not found in your MySQL database.
Connect your database
Follow the steps here to connect your database to your Nanonets account if you haven't already.
Where can I add Validation rules from?
You will be able to add validation rules to your workflow under Approval flow (or Workflows on the left navigation bar). You can add rules against any field in your invoice—if any rule fails, the file will be flagged for manual review and assigned to an approver.
Steps to set up two-way matching with your database
Here's a quick video to help you set this up:
Here are the steps to set this up:
- On the Approval flows page, add team members who will manually review files where the extracted value does not match the value in your database.
(Note: You can select multiple people, we'll assign the flagged file to any one of the selected members)
- Select the label you want to match against your database.
- Choose Match Databases as your validation criteria.
- This will initiate the database configuration steps. This is to specify where in your database this model should look for the data to match with.
- Select the database you added as an integration earlier. (Missed this? Click here)
- Select the table that the data to match with is stored in.
- Once the database and table selection is complete, help us identify matching files with a common field. (like Vendor_ID Nanonets <> vendor ID Database)
Eg: If we extract <invoice number> 123 from your file, we will look for 123 in the <Invoice-number> column in your database. When we find 123, we'll know that all information in that row belongs to invoice 123 (date, address etc)
- Click on Finish database setup when done.
- Once the database configuration is complete, you will be able to choose which column in the database you want the selected field to match.
Once this is complete, click on Done.
Now upload new files to your Extract Data screen. If any entry for the selected field (in the example's case, for Invoice_number) does not match the entry in the chosen column above (In the eg: invoice_number in PostgreSQL), the field and file will be flagged for review.