# Data Products

Manufacturing is complex and so is it's data. In an effort to simplify this data for day to day analysis, the First Resonance team delivers Data Products. These products contain calculations and aggregations that are maintained by the ION Analytics team and served up to ION Analyitcs from optimized data models.

You can rely on these data products to be maintained by First Resonance and optimized for better performance with large datasets. While data will still refresh every 15 minutes—so changes in ION may take that long to appear in analytics—the underlying calculations and joins will be significantly more efficient.

#### **Where can I find these Data Products?**

ION Analytics → Datasets → Pre-Built Datasets.

## :package: Kitting Data Products

These data products support analytics around parts, substitutions, inventory, and fulfillment in the kitting process within manufacturing environments. Each is optimized for self-service usage and integration into broader dashboards or decision models.

### **`part_kit_item_fulfillment`**

**Unique Key**: `(part_kit_id, part_kit_item_id)`\
**Description**:\
This data product captures detailed fulfillment status for each item in a kit. It joins the `part_kit` structure with the individual `part_kit_items`, tracking whether each component within a kit has been sourced, picked, staged, or installed. It is essential for monitoring kit readiness, identifying bottlenecks in staging or fulfillment, and enabling line-side assurance that complete kits are available before work begins.

Use in dashboards and alerts where kit completeness is critical to avoid delays on the production floor.

### **`part_substitutes`**

**Unique Key**: `(part_id, substitute_part_id, mbom_item_id)`\
**Description**:\
Provides a reference of approved substitute parts for any given `part_id` within the context of a specific `mbom_item_id`. This dataset intelligently merges two sources of substitution logic: (1) engineering-driven *mBOM alternatives* and (2) operations-driven *Part Interchangeability* mappings.

This enables planners and operators to make informed substitution decisions when primary parts are unavailable or low in inventory, directly supporting continuity in the kitting process. It's also instrumental in resilience analytics and inventory flexibility strategies.

### **`part_quantities_by_inv_status`**

**Unique Key**: `(part_id)`\
**Description**:\
Aggregates current inventory for each part, grouped by inventory `Status` (e.g., "Available", "Quarantined", "Installed", etc.). This data product gives a snapshot of material readiness by showing how much of each part is practically usable versus allocated, blocked, or consumed.

It supports dynamic kitting readiness assessments, inventory health dashboards, and material shortage projections. Can be joined with demand-based metrics or fulfillment views to create proactive alerting on low-availability parts.<br>

## :ledger: **BOM Data Products**

### **`full_bom`**

#### **Why the Update?**

* Drastically improved load times for dashboards like Clear to Build– reduced from \~2 minutes to \~20 seconds.
  * For large datasets, over 1TB of data can be scanned to gather all the information needed to aggregate plan results.
* Better user experience – simplified access to key supply chain and planning data. ION Analytics → Datasets → Pre-Built Datasets.

#### **What You Need to Do Differently**

* If you use the "Notable Assembly" feature on Clear To Build, ensure it is configured correctly:
  * Set up a "Notable Assembly" attribute at the library level as a text or single-select input.
  * Populate the data accordingly to utilize the relevant dashboard elements.
  * [Full setup instructions](https://manual.firstresonance.io/plans-and-autoplan/clear-to-build-reporting).
* Explore the "full\_bom" dataset for custom analytics needs in ION Analytics → Datasets → Pre-Built Datasets.

## :warning:  Issue Data Products

These data products support analytics around manufacturing issue tracking, triage, and resolution. They unify key context (runs, steps, parts, suppliers) with workflow signals (labels, redlines, related issues, approvals) for faster reporting and easier self-service.&#x20;

Explore the "issue\_details" dataset for analytics needs in ION Analytics → Datasets → Pre-Built Datasets.

***

### issue\_details

**Unique Key / Grain:**

* Primary grain: **one row per issue** (`issue_id`).
* When an issue is linked to part inventory and/or PO line info, the grain can expand; in those cases, treat the compound grain as: **(**`issue_id`, `part_inventory_id`, `purchase_order_line_id`**)**.
* If your dashboard expects strictly one row per issue, either (a) filter to the desired part/PO context, or (b) aggregate back to the issue level.

**Description:**\
A performance-optimized, pre-joined dataset that centralizes the most commonly used fields for issue analysis. It simplifies \~17 joins into a single table and surfaces assignment, lifecycle timestamps, run/step context, related parts & inventory, supplier & PO traceability, labels, redlines, related issues, approval-based resolution date, further-action rollups, attachments, and freshness signals (e.g., days since last update). Ideal for issue queues, SLA tracking, continuous improvement dashboards, and escalation workflows.


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