DataBrighten

    Sample inventory data

    1,000 × 13rows × columns in the 1,000-row file

    Updated 3 November 2026. Fictional U.S. businesses and people, generated with a fixed seed.

    CSV XLSX JSON SQL
    textnumberdateyes/no
    Largest file10,000rows; also 100 and 1,000
    Columns13with a data dictionary below
    Datesno datesrange in the file
    LicenceCC0synthetic, free for any use

    What is in it

    Each row is one SKU in one warehouse: quantity on hand, reorder point and quantity, unit cost and price, stock value, supplier code, last restock date and a needs_reorder flag you can check with a formula.

    First rows

    point at a column to light it up

    skutextproduct_nametextcategorytextwarehousetextquantity_on_handnumberreorder_pointnumberreorder_qtynumberunit_costnumberunit_pricenumberstock_valuenumbersuppliertextlast_restock_datedateneeds_reorderyes/no
    P0001-WH1Mesh Office ChairFurnitureWH1 Newark26760240222.81288.9759490.27SUP-0032024-03-24FALSE
    P0002-WH1Ergonomic Task ChairFurnitureWH1 Newark921836128.43204.7311815.56SUP-0212024-01-09FALSE
    P0003-WH1Stacking Guest ChairFurnitureWH1 Newark601020120.15201.377209SUP-0022024-04-18FALSE
    P0004-WH1Leather Executive ChairFurnitureWH1 Newark1695717136.6669.196195.54SUP-0172024-09-18FALSE
    P0005-WH1Drafting StoolFurnitureWH1 Newark7958116162.35210.1412825.65SUP-0232024-03-17FALSE
    P0006-WH1Rectangular Meeting TableFurnitureWH1 Newark13520159.33208.012071.29SUP-0082024-08-10FALSE
    P0007-WH1Adjustable Standing DeskFurnitureWH1 Newark871938286.01425.9724882.87SUP-0232024-02-13FALSE
    P0008-WH1Round Cafe TableFurnitureWH1 Newark459118164.84216.46659.36SUP-0022024-10-29TRUE
    P0009-WH1Folding Training TableFurnitureWH1 Newark683774238.77326.8716236.36SUP-0042024-05-04FALSE
    P0010-WH15-Shelf BookcaseFurnitureWH1 Newark234814476.53102.421760.19SUP-0062024-08-18TRUE

    Stock value by warehouse

    USD, 1,000-row file

    WH1 Newark$4,470,330WH2 Chicago$3,685,288WH4 Reno$3,350,581WH3 Dallas$3,200,945
    Show as a table
    warehousevalue
    WH1 Newark$4,470,330
    WH2 Chicago$3,685,288
    WH4 Reno$3,350,581
    WH3 Dallas$3,200,945
    Source: DataBrighten synthetic data (seed 42), computed from the file you can download here.

    Data dictionary

    ColumnTypeMeaning
    skutextStock keeping unit (product + warehouse)
    product_nametextGeneric product name
    categorytextProduct category
    warehousetextWarehouse code and city
    quantity_on_handintegerUnits in stock
    reorder_pointintegerReorder when stock falls to this level
    reorder_qtyintegerUnits ordered per restock
    unit_costdecimalCost per unit (USD)
    unit_pricedecimalSelling price per unit (USD)
    stock_valuedecimalquantity_on_hand x unit_cost
    suppliertextFictional supplier code
    last_restock_datedateLast restock (2024)

    Practice questions

    answers checked in SQL and in Python

    How many SKUs need reordering?

    200 SKUs

    Excel

    =SUMPRODUCT(--(E2:E1001<=F2:F1001))

    SQL

    SELECT COUNT(*) FROM inventory WHERE quantity_on_hand <= reorder_point

    File: inventory-1000

    Total stock value by warehouse?

    WH1 Newark $4,470,329.76; WH2 Chicago $3,685,288.21; WH4 Reno $3,350,580.77; WH3 Dallas $3,200,945.35

    Excel

    =SUMIFS(J:J,D:D,"WH1 Newark")

    SQL

    SELECT warehouse, ROUND(SUM(stock_value),2) AS v FROM inventory GROUP BY warehouse ORDER BY v DESC

    File: inventory-1000

    Which category has the highest stock value?

    Technology, $9,825,209.13

    SQL

    SELECT category, ROUND(SUM(stock_value),2) AS v FROM inventory GROUP BY category ORDER BY v DESC LIMIT 1

    File: inventory-1000