The SQL code sample is a query for retrieving invoice data from Oracle Cloud for a specific business unit where the invoice amount is greater than the amount paid. This is a common scenario for accounts payable reporting. Here’s a breakdown of the SQL query:
SELECT
clause retrieves specific columns from various joined tables, renaming some of them using aliases for clarity.FROM
clause specifies the tables you are querying, including ap_invoices_all
, poz_suppliers
, hz_parties
, poz_supplier_sites_all_m
, and fun_all_business_units_v
. These tables are joined using INNER JOIN
statements to link the relevant data.WHERE
clause, several conditions are applied:1 = 1
is a placeholder condition that doesn’t affect the query’s logic but can be used to easily add more conditions.ai.invoice_amount > ai.amount_paid
filters the results to include only invoices where the invoice amount is greater than the amount paid, which is a common condition for open invoices.bu.bu_name = :Business_Unit
filters the results to a specific business unit. :Business_Unit
is a placeholder for a parameter that should be provided when executing the query.This query can be used to retrieve a list of unpaid invoices for a particular business unit in Oracle Cloud. You would need to replace :Business_Unit
with the actual business unit name you want to report on when executing the query.
SELECT
ai.invoice_num invoice_number,
ai.invoice_type_lookup_code invoice_type_code,
ai.invoice_date,
ai.gl_date accounting_date,
hz.party_name supplier_name,
pv.segment1 supplier_number,
pvs.vendor_site_code supplier_site_code,
ai.invoice_currency_code,
ai.invoice_amount,
ai.amount_paid paid_amount
FROM
ap_invoices_all ai
INNER JOIN poz_suppliers pv ON ai.vendor_id = pv.vendor_id
INNER JOIN hz_parties hz ON hz.party_id = pv.party_id
INNER JOIN poz_supplier_sites_all_m pvs ON ai.vendor_site_id = pvs.vendor_site_id
INNER JOIN fun_all_business_units_v bu ON ai.org_id = bu.bu_id
WHERE
1 = 1
AND ai.invoice_amount > ai.amount_paid
AND bu.bu_name = :Business_Unit
Experience swift, user-friendly, and secure data analysis within minutes – directly from Excel.
Copyright © 2024 SplashBI, All rights reserved.