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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.
TableDescription
autoplan_plan_item_resultsAutoplan results grouped by plan item (what to make or buy, quantity, due dates)
autoplan_results_by_plan_inputAutoplan progress and status by plan input
full_bomPlanned and completed work combined for a full production picture
issue_detailsIssues with status plus related redlines and further actions
labor_hoursRun-step durations from start and end times, by run, location, and user
part_kit_item_fulfillmentKit item fulfillment status
part_quantities_by_inv_statusPart quantity by inventory status (Available, WIP, Installed, and others)
part_substitutesApproved part substitution map
planned_bomRecursive planned BOM explosion from MRP and Autoplan demand
query_execution_by_workbookQuery execution metrics per analytics workbook
recursive_abomRecursive aBOM explosion
recursive_mbomRecursive 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.