DataBrighten

    Sample sales data

    1,000 × 19rows × columns in the 1,000-row file

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

    textnumberdateyes/no
    Largest file10,000rows; also 100 and 1,000
    Columns19with a data dictionary below
    Dates2023-01-04 – 2024-12-31range in the file
    LicenceCC0synthetic, free for any use

    What is in it

    Each row is one order line from a fictional U.S. office-supply retailer: date, ship mode, customer, region, product, quantity, discount, sales and profit. Profit can be negative on heavily discounted lines, as in real retail data.

    First rows

    point at a column to light it up

    order_idtextorder_datedateship_datedateship_modetextcustomer_idtextcustomer_nametextsegmenttextregiontextstatetextcitytextcategorytextsub_categorytextproduct_nametextquantitynumberunit_pricenumberdiscountnumbersalesnumbercostnumberprofitnumber
    SO-1000012023-03-222023-03-25Second ClassC0266Patricia MurphyConsumerNortheastNYNew YorkFurnitureFurnishingsDesk Lamp987.180784.62576.27208.35
    SO-1000022024-06-152024-06-21StandardC0386Susan HillConsumerWestCASacramentoTechnologyAccessoriesUSB-C Hub2126.390252.78154.6898.1
    SO-1000032024-01-192024-01-25StandardC0003Stephanie DavisConsumerMidwestMNMinneapolisFurnitureTablesFolding Training Table1326.870326.87238.7788.1
    SO-1000042023-12-052023-12-09Second ClassC0481Donna JacksonCorporateSouthTXDallasOffice SuppliesAppliancesDesk Fan135.16035.1623.0512.11
    SO-1000052023-07-312023-08-03Second ClassC0654Diego HallConsumerMidwestMOKansas CityTechnologyMachinesLaser Printer3473.830.11279.341041.54237.8
    SO-1000062024-01-062024-01-09Second ClassC0204Charles RobinsonConsumerNortheastNYBuffaloOffice SuppliesPaperCardstock 100 Sheets910.7096.358.9537.35
    SO-1000072024-08-262024-08-28Second ClassC0212Ashley NguyenConsumerWestCALos AngelesFurnitureChairsMesh Office Chair1288.970288.97222.8166.16
    SO-1000082024-06-022024-06-06StandardC0724Mei HallConsumerNortheastNYNew YorkTechnologyAccessoriesNoise-Canceling Headset531.860159.310851.3
    SO-1000092024-08-142024-08-17Second ClassC0198Eric CarterConsumerNortheastNJNewarkOffice SuppliesPaperCardstock 100 Sheets310.7032.119.6512.45
    SO-1000102024-11-212024-11-21Same DayC0325Sandra GonzalezConsumerWestCASan FranciscoOffice SuppliesArtDry Erase Markers313.77041.3123.5817.73

    Sales by region

    USD, 1,000-row file

    South$299,380Midwest$234,802West$217,263Northeast$204,169
    Show as a table
    regionvalue
    South$299,380
    Midwest$234,802
    West$217,263
    Northeast$204,169
    Source: DataBrighten synthetic data (seed 42), computed from the file you can download here.

    Data dictionary

    ColumnTypeMeaning
    order_idtextOrder number, unique per row
    order_datedateDate the order was placed (2023-2024)
    ship_datedateDate shipped, 0-6 days after the order
    ship_modetextStandard, Second Class, First Class or Same Day
    customer_idtextCustomer number
    customer_nametextFictional customer name
    segmenttextConsumer, Corporate or Home Office
    regiontextU.S. Census region of the city
    statetextTwo-letter state code
    citytextCity
    categorytextProduct category
    sub_categorytextProduct sub-category

    Practice questions

    answers checked in SQL and in Python

    What are total sales and total profit?

    Sales $955,613.76, profit $214,946.97

    Excel

    =SUM(Q2:Q1001) and =SUM(S2:S1001)

    SQL

    SELECT ROUND(SUM(sales),2), ROUND(SUM(profit),2) FROM sales_orders

    File: sales-orders-1000

    Which region has the highest sales?

    South, $299,380.41 (Midwest $234,801.89, West $217,262.68, Northeast $204,168.78)

    Excel

    =SUMIFS(Q:Q,H:H,"South")  (one region per cell), or a PivotTable: region in Rows, Sum of sales in Values

    SQL

    SELECT region, ROUND(SUM(sales),2) AS total FROM sales_orders GROUP BY region ORDER BY total DESC, region

    File: sales-orders-1000

    Profit margin (profit / sales) by category?

    Office Supplies 26.98%; Technology 22.32%; Furniture 21.42%

    Excel

    =SUMIFS(S:S,K:K,"Technology")/SUMIFS(Q:Q,K:K,"Technology")

    SQL

    SELECT category, ROUND(SUM(profit)/SUM(sales)*100,2) AS margin_pct FROM sales_orders GROUP BY category ORDER BY margin_pct DESC, category

    File: sales-orders-1000

    How many orders had a discount of 30% or more, and what was their combined profit?

    114 orders, combined profit $-8,060.65

    Excel

    =COUNTIFS(P:P,">=0.3") and =SUMIFS(S:S,P:P,">=0.3")

    SQL

    SELECT COUNT(*), ROUND(SUM(profit),2) FROM sales_orders WHERE discount >= 0.3

    File: sales-orders-1000

    Which month had the highest sales?

    2023-02, $69,236.92

    SQL

    SELECT substr(order_date,1,7) AS month, ROUND(SUM(sales),2) AS total FROM sales_orders GROUP BY month ORDER BY total DESC LIMIT 1

    Add a month column (=TEXT(B2,"yyyy-mm") in Excel, or FORMAT in Power BI), then sum sales by it.

    File: sales-orders-1000