Runs quality rules on live master data, routes each failing record to its steward with the fix options, and writes the correction back to the ERP.
Tables are read in place through the native Snowflake connector: the app sends only the filter and the columns it needs, Snowflake returns the matching rows. The Backbone landing model (RAW, CONFORMED and HISTORY schemas) is the usual source, so history and aggregates are already prepared.
| Object | Read from | Fields the app uses | Freshness |
|---|---|---|---|
| Material master | CONFORMED.MATERIAL | status (status) · planned_lead_time (lead time) · material_id (id) · description (desc) | prepared by the Backbone; refreshed on its schedule |
| Supplier master | CONFORMED.VENDOR | payment_terms (terms) · vendor_id (id) · name (name) · country (country) | prepared by the Backbone; refreshed on its schedule |
| Customer master | CONFORMED.CUSTOMER | sales_org (sales org) · customer_id (id) · name (name) · country (country) | prepared by the Backbone; refreshed on its schedule |
| Purchase order line | CONFORMED.PURCHASE_ORDER_LINE · HISTORY.PO_LINE_VERSIONS | po_number (number) · po_line (line) · vendor_id (vendor) · material_id (material) | prepared by the Backbone; refreshed on its schedule |
In plain words: A record that fails one of the active quality rules, such as an active material with a lead time of 0, a supplier with empty payment terms, or a customer with an empty sales organisation.
The criterion runs in Snowflake through the data handler, so only the matching rows return. The editor shows the rows it selects, and their count, as it is written.
# start criterion in Snowflake fields (status = 'active' and planned_lead_time = 0) or payment_terms = '' or sales_org = '' # the same criterion in canonical fields ({material.status} = 'active' and {material.lead_time} = 0) or {vendor.terms} = '' or {customer.sales_org} = ''
Decisions are recorded in a Lima-owned table in Snowflake through stage, COPY INTO and MERGE, so analytics see them next to the history. The operational write goes to the system of record through its released interface, and the app records the acknowledgement. For this app the operational change (field corrected through the material interface) goes to SAP S/4HANA or Oracle Fusion through its released interface, and the pair pages for those systems show the exact call.
| Object | What changes | Interface |
|---|---|---|
| Material master | field corrected through the material interface; exception flag recorded beside the record | MERGE into LIMA.APP_DECISIONS · operational write to the ERP |
| Supplier master | payment terms, country or purchasing data corrected; duplicate flagged for deletion | MERGE into LIMA.APP_DECISIONS |
| Customer master | sales organisation data completed or corrected | MERGE into LIMA.APP_DECISIONS |
Each write stores the identifier Snowflake returns beside the decision, the person and the time, so the log answers who changed what, and the reconciliation shows it arrived.
Snowflake roles and row-access policies are mapped to Lima access policies once, so a person sees the same rows in the app that they see in a worksheet.
This app reads material master from Snowflake because the screens need history at scale: months of rows, aggregates by period, several versions. The Backbone lands the objects in the conformed model and refreshes them on a schedule, and the handler reads them in place with the filter and the columns pushed down. The person's grants in Snowflake decide what they see.
The operational rows the person acts on can come live from the ERP in the same app: one handler per object per system, and a screen that shows both.
The screens read through handlers that leave the rows in Snowflake. The conformed tables it reads were landed there by the Backbone from the ERP; the app reads them there.
The prerequisites above: an integration identity with read rights on the objects listed and write rights on the interfaces named, connectivity, and the scopes agreed with the process owner.
Yes. The screens, criteria and roles stay; the handlers are re-bound to the other system's objects, and the app's other system pages show them.
Bring the process and the systems it touches. In the first session we register the data handlers, draw the levels or the lanes and run the first screen on your live rows.
