Data Products - ION Manual

Data Products

Data Products are views maintained by First Resonance that pre-join and aggregate common queries, so you don’t rebuild the same multi-table joins in every dashboard. Each data product is delivered as a queryable view inside the Data Connector. Use them as the source for your BI dashboards, such as Power BI, Tableau, Looker, or Sigma, or for downstream pipelines. Refresh latency follows the standard Data Connector SLAs.

Data Products are part of the Data Connector offering. If you don’t see them in your warehouse yet, contact your Customer Success Manager about enabling the Data Connector for your organization.

Data Products are the computed tier of the Data Connector. For the raw and cleaned (_enriched) tiers, a near 1:1 replica of every ION entity, see Available tables.

All data products

The complete set of computed views available through the connector. The most commonly used products are documented in detail below.

Table	Description
`autoplan_plan_item_results`	Autoplan results grouped by plan item (what to make or buy, quantity, due dates)
`autoplan_results_by_plan_input`	Autoplan progress and status by plan input
`full_bom`	Planned and completed work combined for a full production picture
`issue_details`	Issues with status plus related redlines and further actions
`labor_hours`	Run-step durations from start and end times, by run, location, and user
`part_kit_item_fulfillment`	Kit item fulfillment status
`part_quantities_by_inv_status`	Part quantity by inventory status (Available, WIP, Installed, and others)
`part_substitutes`	Approved part substitution map
`planned_bom`	Recursive planned BOM explosion from MRP and Autoplan demand
`query_execution_by_workbook`	Query execution metrics per analytics workbook
`recursive_abom`	Recursive aBOM explosion
`recursive_mbom`	Recursive mBOM explosion

Kitting data products

These data products cover parts, substitutions, inventory, and fulfillment in the kitting process.

`part_kit_item_fulfillment`

Unique key: (part_kit_id, part_kit_item_id) Fulfillment status for each item in a kit. It joins the part_kit structure with the individual part_kit_items and tracks whether each component has been sourced, picked, staged, or installed. Use it to monitor kit readiness and find staging or fulfillment bottlenecks before work begins.

`part_substitutes`

Unique key: (part_id, substitute_part_id, mbom_item_id) Approved substitute parts for a given part_id within the context of a specific mbom_item_id. It merges two sources of substitution logic: engineering-driven mBOM alternatives and operations-driven part interchangeability mappings. Planners and operators use it to choose a substitute when the primary part is unavailable or low in inventory.

`part_quantities_by_inv_status`

Unique key: (part_id) Current inventory for each part, grouped by inventory Status (Available, Quarantined, Installed, and others). It shows how much of each part is usable versus allocated, blocked, or consumed. Join it with demand metrics to flag low-availability parts.

BOM data products

`full_bom`

A flattened, multi-level BOM rollup for fast querying of supply chain and planning data. Dashboards that previously joined the BOM tree at query time, such as Clear to Build, can read directly from full_bom for faster load times. To use Notable Assembly with full_bom:

Define a “Notable Assembly” attribute at the part library level (text or single-select).
Populate the attribute on the parts you want flagged.
Configure the attribute name in your Clear-to-Build reporting setup.

Issue data products

These data products cover manufacturing issue tracking, triage, and resolution. They unify run, step, part, and supplier context with workflow signals such as labels, redlines, related issues, and approvals.

`issue_details`

Unique key and grain:

Primary grain: one row per issue (issue_id).
When an issue is linked to part inventory or PO line information, the grain expands. In those cases, treat the compound grain as (issue_id, part_inventory_id, purchase_order_line_id).
If your dashboard expects one row per issue, either filter to the desired part or PO context, or aggregate back to the issue level.

A pre-joined dataset that centralizes the most commonly used fields for issue analysis: assignment, lifecycle timestamps, run and step context, related parts and inventory, supplier and PO traceability, labels, redlines, related issues, approval-based resolution date, further-action rollups, attachments, and freshness signals such as days since last update. Use it for issue queues, SLA tracking, and continuous-improvement dashboards.