M3 Reference
MMS001
InteractiveItem master maintenance — where items are created and their MITMAS attributes managed
Tables vs APIs
This program works over the tables below. For analytics at scale, land the raw tables — the SQL further down reads them directly, joined on their keys and CONO. When to land tables vs call MI APIs →
Boilerplate SQL
Databricks SQLStarting point for reading the tables behind MMS001 from landed data — the backing tables joined on their keys and CONO. Set your Unity Catalog location, company, and filter values below.
Query parameters
-- ============================================================
-- Program: MMS001 — Item master maintenance — where items are created and their MITMAS attributes managed
-- Purpose: Read the tables behind program MMS001 — auto-generated from program-table-map
-- Grain : One row per MITMAS record
-- Tables : MITMAS
-- Notes : Auto-generated skeleton for Infor Data Lake-landed M3 data. Dates are numeric YYYYMMDD (0 = none, mapped to NULL); status ladders decoded inline where verified; company-partitioned tables are joined on CONO to prevent cross-company fan-out. Audit columns (RGDT/RGTM/LMDT/CHNO/CHID) omitted — see the quirks guide.
-- ============================================================
SELECT
im.MMCONO AS "Company",
im.MMITNO AS "Item number — the natural key every balance, order line, and movement joins on",
im.MMITDS AS "Item name (short description)",
im.MMFUDS AS "Item description (full)"
FROM <catalog>.<schema>.MITMAS im
WHERE
im.MMCONO = <company>
ORDER BY im.MMITNO;3 parameters not filled: <catalog>, <schema>, <company>