Logistics
24 columns
70 rows
8 formats

Warehouse Inventory Turnover

This dataset provides detailed records of product inventory turnover across multiple warehouses, capturing product movement, stock levels, and key performance metrics over specified periods. It enables logistics firms to analyze inventory efficiency, optimize stock levels, reduce carrying costs, and minimize out-of-stock events. The dataset is ideal for supply chain optimization, demand forecasting, and warehouse performance benchmarking.

last updated 12 Jul 2025
by GoMask

The brief that made it

Inventory optimization and reduction of carrying costs

Sample rows

preview · 8 of 70 rows · all 24 columns

inventory_record_idstring	warehouse_countrystring	carrying_cost_per_unitfloat	warehouse_statestring	warehouse_idstring	warehouse_namestring	warehouse_street_addressstring	warehouse_citystring	warehouse_postal_codestring	product_idstring	product_namestring	product_categorystring	skustring	inventory_period_startdate	inventory_period_enddate	beginning_inventory_qtyinteger	ending_inventory_qtyinteger	units_receivedinteger	units_shippedinteger	units_returnedinteger	average_inventory_qtyfloat	inventory_turnover_ratefloat	stockout_eventsinteger	notesstring
INV10001	USA	0.15	TX	WH001	Central Distribution	123 Main St	Dallas	75201	P1001	UltraClean Detergent	Cleaning Supplies	UC-1001	2024-01-01	2024-01-31	500	350	200	340	5	425	0.8	1	Higher than average demand mid-month
INV10002	USA	0.08	CA	WH002	Pacific Hub	456 Ocean Ave	San Francisco	94111	P1002	EcoPaper Towels	Paper Goods	EP-5550	2024-01-01	2024-01-31	200	120	100	170	2	160	1.06	0	blank
INV10003	USA	0.22	IL	WH003	Midwest Fulfillment	789 Prairie Rd	Chicago	60607	P1003	Allergy Relief Tablets	Health	AR-2021	2024-01-01	2024-01-31	300	285	50	60	0	292.5	0.21	0	blank
INV10004	USA	0.12	NY	WH004	East Coast Depot	135 Harbor Blvd	New York	10004	P1004	Organic Trail Mix	Food	OTM-300	2024-01-01	2024-01-31	100	80	60	70	0	90	0.78	0	blank
INV10005	USA	0.1	TX	WH001	Central Distribution	123 Main St	Dallas	75201	P1005	Reusable Water Bottle	Household	WB-2024	2024-01-01	2024-01-31	350	310	80	120	1	330	0.36	0	blank
INV10006	USA	0.18	AZ	WH005	Southwest Logistics	220 Desert Dr	Phoenix	85001	P1006	LED Light Bulb	Electronics	LED-4500	2024-01-01	2024-01-31	600	510	150	240	4	555	0.43	0	blank
INV10007	USA	0.14	CA	WH002	Pacific Hub	456 Ocean Ave	San Francisco	94111	P1007	Wireless Mouse	Electronics	WM-9001	2024-01-01	2024-01-31	250	180	100	160	3	215	0.74	0	Promotion increased sales
INV10008	USA	0.1	IL	WH003	Midwest Fulfillment	789 Prairie Rd	Chicago	60607	P1008	Protein Bars - Choco	Food	PB-CH-20	2024-01-01	2024-01-31	120	70	80	130	2	95	1.37	1	blank
INV10009	USA	0.09	NY	WH004	East Coast Depot	135 Harbor Blvd	New York	10004	P1009	Children's Multivitamin	Health	MV-KIDS-01	2024-01-01	2024-01-31	400	350	60	110	2	375	0.29	0	blank
INV10010	USA	0.23	AZ	WH005	Southwest Logistics	220 Desert Dr	Phoenix	85001	P1010	Bluetooth Earbuds	Electronics	BE-1002	2024-01-01	2024-01-31	180	120	70	130	1	150	0.87	0	blank
INV10011	USA	0.13	MN	WH006	Northern Storage	22 Maple Lane	Minneapolis	55401	P1001	UltraClean Detergent	Cleaning Supplies	UC-1001	2024-01-01	2024-01-31	420	410	30	35	0	415	0.08	0	blank
INV10012	USA	0.09	MA	WH007	Atlantic Storage	14 Seaside Ave	Boston	02110	P1002	EcoPaper Towels	Paper Goods	EP-5550	2024-01-01	2024-01-31	100	60	50	85	1	80	1.06	0	blank
INV10013	USA	0.07	MN	WH006	Northern Storage	22 Maple Lane	Minneapolis	55401	P1011	Granola Cereal	Food	GC-1111	2024-01-01	2024-01-31	80	75	10	15	0	77.5	0.19	0	blank
INV10014	USA	0.11	TX	WH001	Central Distribution	123 Main St	Dallas	75201	P1012	Stainless Steel Lunchbox	Household	SSLB-2020	2024-01-01	2024-01-31	90	40	50	100	0	65	1.54	2	Stockout occurred in last week
INV10015	USA	0.13	NY	WH004	East Coast Depot	135 Harbor Blvd	New York	10004	P1013	Vitamin D3 Supplements	Health	VD3-777	2024-01-01	2024-01-31	110	90	40	60	0	100	0.6	0	blank
INV10016	USA	0.17	CA	WH002	Pacific Hub	456 Ocean Ave	San Francisco	94111	P1006	LED Light Bulb	Electronics	LED-4500	2024-01-01	2024-01-31	320	315	40	45	0	317.5	0.14	0	blank
INV10017	USA	0.08	IL	WH003	Midwest Fulfillment	789 Prairie Rd	Chicago	60607	P1014	Organic Apple Juice	Food	OAJ-007	2024-01-01	2024-01-31	70	60	30	40	0	65	0.62	0	blank
INV10018	USA	0.12	AZ	WH005	Southwest Logistics	220 Desert Dr	Phoenix	85001	P1015	Antibacterial Wipes	Cleaning Supplies	AW-9000	2024-01-01	2024-01-31	250	200	60	100	1	225	0.44	0	blank
INV10019	USA	0.1	MN	WH006	Northern Storage	22 Maple Lane	Minneapolis	55401	P1016	Oat Milk 1L	Food	OM-1L-022	2024-01-01	2024-01-31	95	60	50	85	1	77.5	1.1	1	blank
INV10020	USA	0.13	MA	WH007	Atlantic Storage	14 Seaside Ave	Boston	02110	P1017	Natural Conditioner	Personal Care	NC-500	2024-01-01	2024-01-31	60	40	30	50	0	50	1	0	blank

What the 70 rows show

from the 70-row sample

USA (warehouse country) stands out: mean carrying_cost_per_unit is 0.28, against 0.89 for the rest.

0.23median carrying_cost_per_unit
15warehouse cities
16warehouses
16warehouse names
16warehouse street addresses
16warehouse postal codes

Mean carrying_cost_per_unit by warehouse_country70 rows

carrying_cost_per_unit70 rows, in bands of 0.25

Median 0.23, from 0.06 to 2.4.

warehouse_state66 rows with a value · 4 left blank

TX10
CA9
IL5
NY5
AZ5
MN5
MA4
MB4
England4
Berlin4

24 columns by typefrom the column list below

string 13
integer 6
float 3
date 2

Columns

24 columns in three groups

blueprint · 24 columns
column	type	description	example
Text 13 columns
`inventory_record_id`	string	Unique identifier for each inventory turnover recordunique	INV10001
`warehouse_id`	string	Unique identifier for the warehouse where the product is stored	WH001
`warehouse_name`	string	Name of the warehouse	Central Distribution
`warehouse_street_address`	string	Street address of the warehouseoptional	123 Main St
`warehouse_city`	string	City where the warehouse is locatedoptional	Dallas
`warehouse_state`	string	State or province where the warehouse is locatedoptional	TX
`warehouse_postal_code`	string	Postal code of the warehouse locationoptional	75201
`warehouse_country`	string	Country where the warehouse is located8 countries · optional	USA
`product_id`	string	Unique identifier for the product	P1001
`product_name`	string	Name or description of the product	UltraClean Detergent
`product_category`	string	Category or type of the productoptional	Cleaning Supplies
`sku`	string	Stock Keeping Unit (SKU) for the productoptional	UC-1001
`notes`	string	Additional notes or comments about the inventory recordoptional	Clearance sale.
Numbers 9 columns
`beginning_inventory_qty`	integer	Quantity of product in inventory at the beginning of the period0 or more	500
`ending_inventory_qty`	integer	Quantity of product in inventory at the end of the period0 or more	350
`units_received`	integer	Total number of units received into inventory during the period0 or more	200
`units_shipped`	integer	Total number of units shipped out of inventory during the period0 or more	340
`units_returned`	integer	Total number of units returned to inventory during the period0 or more · optional	5
`average_inventory_qty`	float	Average inventory quantity during the period ((beginning + ending) / 2)0 or more	425
`inventory_turnover_rate`	float	Inventory turnover rate for the period (units shipped / average inventory)0 or more	0.8
`stockout_events`	integer	Number of times the product was out of stock during the period0 or more · optional	1
`carrying_cost_per_unit`	float	Estimated carrying cost per unit for the product during the period0 or more · optional	0.15
Dates and times 2 columns
`inventory_period_start`	date	Start date of the inventory tracking period	2024-01-01
`inventory_period_end`	date	End date of the inventory tracking period	2024-01-31

Use it for

A logistics dashboard
Carrying_cost_per_unit by warehouse_country and a breakdown of warehouse_state. Excel, Power BI or Tableau.
Why do the 43 USA rows have a mean carrying_cost_per_unit of 0.28?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Inventory records70
INV100010.15USA
INV100020.08USA
INV100030.22USA
A software demo
Believable inventory records with warehouse_id, warehouse_name and warehouse_street_address to fill a screen in front of a buyer.

This dataset70 rows24 columns

Yours1,000 rows24 columnswarehouse_street_address: UK only

blueprint · warehouse-inventory-turnover

Behind this dataset

Same schema. As many rows as you need.

These 70 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

Inventory counts taken weekly
Items with 0 turnover in 3 months flagged
Stock-outs over 2 days escalated
Spoiled or damaged goods logged separately

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: warehouse-inventory-turnover

What should your data show?

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Sample rows

What the 70 rows show

Columns

Use it for

A logistics dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?