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LMNT_Discovery_Memo_Ware2Go

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LMNT — Data source discovery memo — Ware2Go (Snowflake RAW.POLYTOMIC_WARE2GO)

Client: LMNT · Audience: Leadership, Analytics, Engineering · Warehouse: Snowflake account OZ69039, database RAW · Profiled: 2026-04-14 (Snowflake CLI lmnt_service; INFORMATION_SCHEMA; ORDERS.ORDER_DATE profiling)

Executive summary

Ware2Go is a third-party logistics platform. The extract includes fulfillment orders, inventory, inbound shipments, returns (RMAs), and reference tables. Data lives in RAW.POLYTOMIC_WARE2GO.

ORDERS profiling (ORDER_DATE, non-deleted rows): roughly 1.21M rows from 2025-07-15 through 2026-01-13. INFORMATION_SCHEMA may estimate ~1.55M rows—use live queries for board numbers and document filters. If LMNT uses Stord for current fulfillment, treat Ware2Go as historical or transitional unless Operations confirms ongoing dual feed.

Access and lineage

Ware2Go → Polytomic → RAW.POLYTOMIC_WARE2GO. Confirm whether the sync still receives new events.

Per-table catalog

Each table below lists metrics, business objective, and questions this table answers.

ORDERS

  • Metrics: ~1.21M–1.55M rows depending on estimate vs analytical filter. ORDER_DATE (profiling): 2025-07-15 to 2026-01-13 on non-deleted rows.
  • Business objective: 3PL fulfillment orders from Ware2Go for operations and historical performance.
  • Questions this table answers:
    • How many fulfillment orders ran through Ware2Go in a week or month?
    • How does volume trend during the Ware2Go period?
    • How do Ware2Go order ids map to Shopify order ids (requires Ops mapping)?

RMAS

  • Metrics: ~6,219 rows.
  • Business objective: Return merchandise authorizations for reverse logistics.
  • Questions this table answers:
    • What return volume flowed through Ware2Go?
    • How do RMAs tie to original outbound orders for net fulfillment metrics?

INBOUND_SHIPMENTS

  • Metrics: ~3,616 rows.
  • Business objective: Inbound shipments into Ware2Go facilities.
  • Questions this table answers:
    • What inbound volume arrived in a period?
    • How does inbound relate to purchase or transfer plans (outside this schema)?

INVENTORY

  • Metrics: ~270 rows.
  • Business objective: Inventory positions or snapshots (confirm column grain—SKU by location, etc.).
  • Questions this table answers:
    • What on-hand or available quantity did Ware2Go report at a point in time?
    • How should we aggregate without double-counting (snapshot vs event)?

SALES_CHANNELS

  • Metrics: ~30 rows.
  • Business objective: Channel reference for tagging or routing orders.
  • Questions this table answers:
    • Which named sales channels exist for Ware2Go orders?
    • How do channels slice fulfillment volume?

TAGS

  • Metrics: ~9 rows.
  • Business objective: Tags for categorizing orders or accounts in Ware2Go.
  • Questions this table answers:
    • What tag vocabulary is used for filtering operational reports?
    • How do tags correlate with channel or priority?

WAREHOUSE_MATCHES

  • Metrics: ~6 rows.
  • Business objective: Mapping between warehouse or system identifiers (confirm with Ops).
  • Questions this table answers:
    • How are Ware2Go locations or codes aligned to internal names?
    • What bridges exist for cross-system joins?

Joins and caveats

  • Use RAW.POLYTOMIC_STORD for current network fulfillment if Operations has cut over.
  • Document cutover date between Ware2Go and Stord for inventory and fill-rate KPIs.
  1. Label Ware2Go-dependent dashboards legacy if no longer operationally active.
  2. Record as-of date if sync stops.
  3. Document Shopify ↔ Ware2Go order mapping where maintained outside Snowflake.

Graph View