생성기
모의 데이터 생성기 (Pro)
25+ field types — names, addresses, products, finance, lorem.
Runs in your browser
Schema · 8 field(s)
[
{
"id": "41936071-dfd7-ad91-2fee-8284fd2d7008",
"name": "Joan Clarke",
"email": "tony.knuth58@example.com",
"city": "Singapore",
"company": "Cyberdyne",
"joined_at": "2025-09-04",
"amount": "$990.29",
"active": true
},
{
"id": "1372c9c6-3404-5ef3-d955-2f1ec6b41813",
"name": "Hedy Hoare",
"email": "edsger.torvalds22@example.com",
"city": "Singapore",
"company": "Pied Piper",
"joined_at": "2025-07-30",
"amount": "$697.47",
"active": false
},
{
"id": "6228af6b-601d-fc26-47de-358460a5749b",
"name": "Ken Lamarr",
"email": "linus.knuth41@example.com",
"city": "Seoul",
"company": "Wayne Enterprises",
"joined_at": "2025-06-22",
"amount": "$949.99",
"active": false
},
{
"id": "e0488ffb-d49a-057c-f094-aa74b80dbeb8",
"name": "Brian Kernighan",
"email": "hedy.wirth5@example.com",
"city": "Mumbai",
"company": "Tyrell",
"joined_at": "2026-02-22",
"amount": "$747.48",
"active": true
},
{
"id": "f7599069-1214-486f-a95b-4ee8ab942315",
"name": "Frances Wirth",
"email": "hedy.clarke29@example.com",
"city": "Singapore",
"company": "Wonka",
"joined_at": "2026-01-15",
"amount": "$730.83",
"active": false
},
{
"id": "ca4cfce2-98b0-60d3-6fa9-179e22dfc13c",
"name": "Brendan Eich",
"email": "joan.hopper67@example.com",
"city": "Seoul",
"company": "Tyrell",
"joined_at": "2025-10-26",
"amount": "$890.89",
"active": false
},
{
"id": "c7c37932-62ca-331d-f661-1d4795b43fc0",
"name": "Joan Turing",
"email": "margaret.hamilton92@example.com",
"city": "Helsinki",
"company": "Soylent",
"joined_at": "2026-05-06",
"amount": "$784.58",
"active": true
},
{
"id": "e0b1b44d-b0d2-3b26-fc78-b308af36e94e",
"name": "Brian Lamarr",
"email": "hedy.kernighan34@example.com",
"city": "Tokyo",
"company": "Hooli",
"joined_at": "2025-11-05",
"amount": "$90.80",
"active": true
},
{
"id": "bdac7c22-6843-00c5-77d6-8d4928374f6c",
"name": "Brian Thompson",
"email": "joan.hamilton39@example.com",
"city": "Lisbon",
"company": "Tyrell",
"joined_at": "2026-03-03",
"amount": "$547.09",
"active": true
},
{
"id": "f52bcf8a-2c65-eda4-9220-b3c7ab108bd5",
"name": "Donald Kernighan",
"email": "margaret.wirth21@example.com",
"city": "Lisbon",
"company": "Stark Industries",
"joined_at": "2026-01-28",
"amount": "$288.01",
"active": false
},
{
"id": "c4a510e8-7e6d-2673-e4f5-911c2eba6305",
"name": "Niklaus Allen",
"email": "alan.hopper55@example.com",
"city": "Mumbai",
"company": "Stark Industries",
"joined_at": "2026-05-02",
"amount": "$866.81",
"active": true
},
{
"id": "fbec4928-ab73-99ee-417d-e995cccc57b6",
"name": "Donald Turing",
"email": "joan.dijkstra34@example.com",
"city": "Sydney",
"company": "Stark Industries",
"joined_at": "2025-11-04",
"amount": "$960.94",
"active": true
},
{
"id": "8496823a-f2be-9696-c839-e0a1b2be3d3e",
"name": "Linus Hopper",
"email": "tony.allen45@example.com",
"city": "Tokyo",
"company": "Globex",
"joined_at": "2026-04-08",
"amount": "$331.08",
"active": false
},
{
"id": "ef5d89ef-6817-4d1c-b1ad-7d7883ed5dcb",
"name": "Edsger Dijkstra",
"email": "donald.wirth26@example.com",
"city": "Tokyo",
"company": "Globex",
"joined_at": "2026-03-28",
"amount": "$265.91",
"active": false
},
{
"id": "88d15279-8b78-76b5-b759-6eea802b4435",
"name": "Ada Allen",
"email": "margaret.turing88@example.com",
"city": "Mumbai",
"company": "Stark Industries",
"joined_at": "2025-09-09",
"amount": "$927.74",
"active": false
},
{
"id": "c7dbfa58-5868-25b5-7f4a-9538ebfb4924",
"name": "Niklaus Kernighan",
"email": "hedy.dijkstra91@example.com",
"city": "Tokyo",
"company": "Hooli",
"joined_at": "2026-05-10",
"amount": "$837.78",
"active": true
},
{
"id": "97b61316-f8f8-2c0d-b2ee-98745f43e2b0",
"name": "Joan Hamilton",
"email": "hedy.lovelace72@example.com",
"city": "London",
"company": "Hooli",
"joined_at": "2025-11-01",
"amount": "$767.56",
"active": true
},
{
"id": "b1b3721e-23cd-bca4-c3f6-13df560fff6c",
"name": "Donald Hamilton",
"email": "margaret.knuth11@example.com",
"city": "Singapore",
"company": "Initech",
"joined_at": "2025-11-22",
"amount": "$598.82",
"active": false
},
{
"id": "5929db2c-0b5f-41f3-72f1-03590f4d9141",
"name": "Grace Kernighan",
"email": "alan.eich49@example.com",
"city": "Toronto",
"company": "Initech",
"joined_at": "2025-07-09",
"amount": "$793.65",
"active": true
},
{
"id": "1b9f10b4-b426-3c93-8b17-c2feed886779",
"name": "Alan Allen",
"email": "linus.hamilton73@example.com",
"city": "Seoul",
"company": "Tyrell",
"joined_at": "2026-03-19",
"amount": "$122.16",
"active": false
}
]편집자 노트
Understanding · Realistic-looking data, generated to fit a schema.
이 심층 챕터는 현재 영어로만 제공됩니다. 위의 변환 도구는 귀하의 언어로 작동하지만, 긴 설명 글은 아직 번역되지 않았습니다.
자주 묻는 질문
Quick answers.
›What data formats can I export?
The generator supports JSON, CSV, and SQL insert statements. You can also copy individual rows or the entire dataset directly to your clipboard.
›How many records can I generate at once?
You can generate up to 5,000 records per batch. Large batches are processed in your browser memory, so performance depends on your device hardware.
›Is the generated data truly random?
Yes. It uses a library of realistic values combined with randomisation to ensure variety in names, addresses, and secondary fields like `UUID` or `Lorem Ipsum` text.
›Can I define custom fields?
Select from over 25 predefined field types including personal details, commerce data, and technical identifiers. You can rename headers to match your specific database columns.
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