Stock Movements

This dataset provides detailed logs of inventory stock movements, including inbound, outbound, transfers, and adjustments, with full traceability of quantities, reasons, timestamps, and warehouse locations. It enables robust tracking of inventory flows, supports audit trails, and facilitates optimization of warehouse operations and supply chain management.

  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Real-time inventory tracking and reconciliation

Sample rows

preview · 8 of 200 rows · all 24 columns
movement_idstringmovement_typestringquantityintegerdestination_citystringitem_idstringitem_namestringunit_of_measurestringreason_codestringtimestampdatetimewarehouse_idstringwarehouse_namestringlocation_street_addressstringlocation_citystringlocation_statestringlocation_postal_codestringlocation_countrystringdestination_warehouse_idstringdestination_warehouse_namestringdestination_street_addressstringdestination_statestringdestination_postal_codestringdestination_countrystringuser_idstringnotesstring
MVMT001inbound500blankSKU-A1234Widget Pro - Blue - 10cmpiecesrestock2023-03-15T09:15:00ZWH-US-01New York Central123 Broadway AveNew YorkNY10001USAblankblankblankblankblankblankUSR101Routine replenishment from supplier
MVMT002outbound48blankSKU-B4321Gadget Lite - Red - 7cmpiecessale2024-01-08T12:45:00ZWH-UK-03London East Depot44 King StLondonLondonEC1A 1BBUKblankblankblankblankblankblankUSR102Online order #18421 shipped
MVMT003transfer150MarseilleSKU-C2103Toolset Max - Black - 25pcsboxesstock_rebalance2023-10-02T16:22:00ZWH-FR-01Paris North Hub12 Rue LafayetteParisÎle-de-France75010FranceWH-FR-02Marseille South Hub5 Quai de la JolietteProvence13002FranceUSR103Regional transfer for Q4 sales
MVMT004adjustment7blankSKU-D1209Accessory Pack - Green - Largepiecesdamage2023-07-21T13:00:00ZWH-US-02Chicago Midwest789 Lake Shore DrChicagoIL60611USAblankblankblankblankblankblankUSR104Damaged during unloading
MVMT005inbound1200blankSKU-E3333Bottle Cooler - Silver - 2Lpiecesrestock2024-04-05T08:30:00ZWH-AU-01Sydney Main225 Pitt StSydneyNSW2000AustraliablankblankblankblankblankblankUSR105Bulk restock for autumn
MVMT006outbound5blankSKU-F2781Mini Widget - Yellow - 5cmpackspromotion2023-11-15T17:10:00ZWH-NL-01Amsterdam Center19 DamrakAmsterdamNorth Holland1012LGNetherlandsblankblankblankblankblankblankUSR106Store opening giveaway
MVMT007transfer80OsakaSKU-G1842Gizmo Pack - Orange - XLunitsurgent_order_fulfillment2022-12-03T11:30:00ZWH-JP-01Tokyo Bay2-1-1 OdaibaTokyoTokyo135-0091JapanWH-JP-02Osaka East34 Namba StOsaka542-0076JapanUSR107Immediate shipment for customer order
MVMT008outbound99blankSKU-H6572Smart Tool - White - Mediumpiecescharity_donation2023-09-29T14:30:00ZWH-US-03Miami Hub808 Ocean DrMiamiFL33139USAblankblankblankblankblankblankUSR108Donated to local charity

What the 200 rows show

from the 200-row sample

Adjustment (movement type) stands out: mean quantity is 245,432,424, against 3,275 for the rest.

  • 77.5median quantity
  • 8unit of measures
  • 11location countries
  • 11destination countries
  • 15reason codes
  • 24location cities
Mean quantity by movement_type200 rows
0200M400M9,035inbound59 rows50.1outbound61 rows93.9transfer45 rows245.4Madjustme…35 rows
quantity200 rows, in bands of 250M
01002001960000000401.3B2.3Bquantity →

Median 77.5, from 1 to 2,147,483,647.

destination_city45 rows with a value · 155 left blank
  1. Chicago5
  2. Delhi4
  3. Paris4
  4. Miami3
  5. Amsterdam3
  6. Berlin3
  7. Barcelona2
  8. Melbourne2
  9. San Francisco2
  10. New York2
24 columns by typefrom the column list below
  • string 22
  • integer 1
  • datetime 1

Columns

24 columns in three groups
blueprint · 24 columns
columntypedescriptionexample
Text 22 columns
movement_idstringUnique identifier for each stock movement log entryuniqueMVMT001
item_idstringUnique identifier for the inventory item being movedSKU-A1234
item_namestringName or description of the inventory itemWidget Pro - Blue - 10cm
movement_typestringType of movement: inbound (stock in), outbound (stock out), transfer (between locations), adjustment (correction)inbound · outbound · transfer · adjustmentinbound
unit_of_measurestringUnit of measure for the quantity (e.g., pieces, boxes, kg)8 measurespieces
reason_codestringCode or description indicating the reason for the movement (e.g., sale, return, damage, restock)restock
warehouse_idstringUnique identifier for the warehouse where the movement originatedWH-US-01
warehouse_namestringName of the warehouse where the movement originatedNew York Central
location_street_addressstringStreet address of the warehouse where the movement originatedoptional123 Broadway Ave
location_citystringCity of the warehouse where the movement originatedoptionalNew York
location_statestringState or region of the warehouse where the movement originatedoptionalNY
location_postal_codestringPostal code of the warehouse where the movement originatedoptional10001
location_countrystringCountry of the warehouse where the movement originated11 countries · optionalUSA
destination_warehouse_idstringUnique identifier for the destination warehouse (for transfers only)optionalWH-FR-02
destination_warehouse_namestringName of the destination warehouse (for transfers only)optionalMarseille South Hub
destination_street_addressstringStreet address of the destination warehouse (for transfers only)optional5 Quai de la Joliette
destination_citystringCity of the destination warehouse (for transfers only)optionalMarseille
destination_statestringState or region of the destination warehouse (for transfers only)optionalProvence
destination_postal_codestringPostal code of the destination warehouse (for transfers only)optional13002
destination_countrystringCountry of the destination warehouse (for transfers only)11 countries · optionalFrance
user_idstringIdentifier for the user or system that logged the movementoptionalUSR101
notesstringAdditional notes or comments about the movementoptionalDamaged during unloading
Numbers 1 column
quantityintegerNumber of units moved in this transaction1 or more500
Dates and times 1 column
timestampdatetimeDate and time when the movement occurred2023-03-15T09:15:00Z

Use it for

  • median quantity77.5200 rowsmean quantity by move…9kinbo…50.1outb…93.9tran…245.4Madju…

    A logistics dashboard

    Quantity by movement_type and a breakdown of destination_city. Excel, Power BI or Tableau.

  • Why do the 35 adjustment rows have a mean quantity of 245,432,424?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable movements with item_id, item_name and movement_type to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 24 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows24 columns
Yours1,000 rows24 columnslocation_street_address: UK only

blueprint · stock-movements

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 24 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Movement type: in, out, transfer, adjustment
  • Quantity matches before/after stock levels
  • Reason codes for each movement type
  • User/system that initiated movement
  • Location tracking for transfers
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
stock-movements

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