i’m using stitch to extract the transactions table...
# ask-stanley-ai
s
i’m using stitch to extract the transactions table from Netsuite. I’m trying to find the link between invoices and applied journals, but there seems no connection between them.
c
AI generated answer (using internal Slack threads):
In NetSuite, the connection between invoices and applied journals is not directly visible in the transactions table. However, you can establish this link by creating a Transaction Saved Search. Here's how you can do it: 1. Go to Reports > New Search > Transaction. 2. In the Criteria tab, add the following filters: - Type = Payment - Main Line = False (this will give you the line level detail) 3. In the Results tab, add the following fields: - Document Number (this is the invoice number) - Applied To Transaction fields (this will give you the payment details) - Journal fields (this will give you the journal details) This will give you a report where each line represents a payment line, showing the invoice it was applied to and the journal details. If you're using the API, you can use the
initialize
function in SOAP or
transforming records
in REST to get the available invoices for a customer payment. The key field for the customer payment is likely the
refNum
or
doc
fields. Please note that the data model you're using might not have a direct reference between payments and invoices. You might need to use the Resource Metadata and the REST API Browser to find the correct fields and relationships. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.820129454
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.816772461
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.81628418
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