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Supply Chain & Retail Solutions release notes
  • Inventory management solution release notes
    • 2026
      • October 2026
      • September 2026
      • August 2026
      • July 2026
      • June 2026
      • May 2026
      • April 2026
  • Commercial pricing solution release notes
  • Merchandising solution release notes
  • Rebuy & replenishment solution release notes
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September 2026

September 2026 release notes for Inventory Management in Automation Cloud.

September 28, 2026​

Data model updates​

  • Refreshed field descriptions for clarity.

September 24, 2026​

Data requirements tables: new Constraint column​

The dataset reference tables now use a single Constraint column in place of the previous Nullable and Notes columns. It shows each field's role and value rules together — Primary key, Unique, Foreign key to <dataset>, and whether the value is Non-null or Nullable — so a field's constraints are visible at a glance. Any field notes previously in the Notes column have been folded into the field descriptions.

September 17, 2026​

Changed: one email per person for each validation run​

A validation run that fails several checks now sends one email to each person, covering every failure they should see. Previously each failing check sent its own email to every channel named on it, so someone named on two alert channels could receive several emails for one run.

Inside the email, failures are grouped by check, with a row for each column or constraint that failed. A run that fails more than 10 checks lists the first 10 and keeps errors ahead of warnings.

Alerts also now carry the error code for each failure, and the check names what it ran on — Freshness (order_date) rather than Freshness — so two checks of the same type on one table can be told apart. Foreign-key checks can be alerted on in the same way. Slack is unchanged and still sends one message per failing check. See Data quality alerts.

September 16, 2026​

Data model updates​

  • Refreshed field descriptions for clarity.

September 15, 2026​

Data requirements tables updated​

The dataset reference tables have been streamlined and brought fully in line with the solution schema: field descriptions refreshed, previously undocumented fields added, and the "Use" column removed.

Foreign-key results in the Data Quality Dashboard​

Foreign-key checks now report into the Data Quality Dashboard under DI_{E|W}_23F01. A new FK validation issue rows panel lists the rows kept with an unresolved reference and the constraint each one breaks. The object-validation view gains an Async foreign-key checks panel showing the latest run per table.

Counts come from the table's live PEAKAUDITERRORS column, so flagged rows join the failure and warning totals and drop out once an async_foreign_key run clears them. Enabling the check therefore lowers the pass rate for tables with unresolved references. Each violation also carries a new flaggedAt timestamp recording when it was first seen.

September 11, 2026​

Clearer Data requirements pages​

The Data requirements pages now open with a plain-language summary of what the solution does with your data, and list what each dataset is used for — making it easier to see what to prepare before onboarding.

September 1, 2026​

New: order-independent foreign-key checks with keep-and-flag​

A row whose only problem is an unresolved foreign-key reference is now kept in the destination table and flagged in its PEAKAUDITERRORS column instead of being moved to <table_name>_failed_rows. A new async_foreign_key validation re-checks the whole table after rollout and clears a row once its parent is loaded — so tables no longer have to be ingested parent-before-child.

The existing foreign_key check still runs during ingestion. Both accept an optional severity and a params.constraintName array to route constraints per check, and report violations under the new DI_{E|W}_23F01 code. See Object-level validations.

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