Build an invoice dataset in NetSuite Analytics

Build a NetSuite invoice dataset with Type and Main Line criteria. Add customer, location and currency columns, then save and reopen the definition.

The quick answer

Create a Transaction dataset, filter Type to Invoice and Transaction Line: Main Line to Yes, then add Location and Currency. Rename Entity to Customer, save, and reopen the criteria and columns.

The screenshots show a recorded demonstration with sample data. Use your own records and values when following the steps.

Before you start

Use SuiteAnalytics Workbook access to create and edit datasets and permission to read the required transaction fields. Main Line is in the Transaction Line join. Extra one-to-many joins can multiply rows; this example does not create a workbook or share the dataset.

01. Inspect the mixed transaction preview

Open Analytics → Datasets → New Dataset and select Transaction. The starting preview has three invoices and purchase order PO9675. This gives a visible baseline for the invoice criterion.

The unfiltered Transaction dataset contains invoices and a purchase order.

02. Filter Type to Invoice

Drag Transaction Type into the criteria area. Use Field Values, any of, select Invoice and Apply. The purchase order disappears and three invoices remain.

Type is Invoice removes the purchase order from the dataset.

03. Add the joined Main Line criterion

Select Transaction Line, then drag Main Line into criteria. Choose Yes and Apply. Read the AND criteria together. The row count stays at three in this example. Main Line is not a universal duplicate-removal rule.

The criteria combine Invoice with Transaction Line Main Line true.

04. Add location and currency context

Drag Location from Transaction Line into the columns. Switch to Transaction and add Currency, then clear the field search. Rename Entity to Customer through its column menu. Scroll across to check Customer, Transaction Line: Location and Currency. Currency identifies the transaction currency; it does not convert amounts.

The Entity column has been renamed Customer. The final reopened view shows Location and Currency.

05. Save a named dataset

Click Save, enter Invoice Header Review and the description Invoice header context for receivables analysis, then Save in the dialog. This stores the dataset definition without creating a workbook.

The dataset is saved under Invoice Header Review.

06. Reopen and verify the definition

Return to Analytics → Datasets and reopen Invoice Header Review. Compare both AND criteria, the Customer alias, Location and Currency, and the same three invoices.

The reopened dataset retains its invoice criteria and context columns.

Check the result

  1. Both invoice and main-line criteria persist.
  2. Customer, Transaction Line: Location and Currency are retained.
  3. The result remains three invoices; no workbook or access grant was created.

Common questions

How do I create a dataset containing only invoices?

Create a dataset with Transaction as the root record type. Add Transaction: Type = Invoice as a criterion, then add Transaction Line: Main Line = Yes so the dataset uses invoice main-line context.

Where is Main Line in a Transaction-root dataset?

Main Line is under the related Transaction Line record type, not under Transaction. Add it as a criterion and set it to Yes; this selects main-line context but is not a universal duplicate-removal rule.

How do I add customer, location, and currency columns?

Add Transaction Line: Location and Transaction: Currency to the result columns. Rename the Entity column to Customer to change its label; this does not rename the underlying field or customer record. Because Location comes from a joined line record, additional one-to-many joins can change the row count.

What is the difference between saving a dataset and creating a workbook?

Saving preserves the dataset’s records, criteria, columns, and aliases for reuse. It does not create a workbook, change transactions, or grant access to another user; a workbook must be created separately and sharing must be configured separately.

Supporting sources

Supporting documentation.