Datasets:

ziadatalabs
/

FreeCustomerData50M

license: cc-by-nc-4.0
task_categories:
  - tabular-classification
  - tabular-regression
language:
  - en
tags:
  - synthetic
  - test-data
  - mock-data
  - customer-data
  - tabular
  - faker
size_categories:
  - 10M<n<100M
pretty_name: Free Synthetic Customer Data (50M)

Free Synthetic Customer Data — 50M Rows

A free, fully synthetic dataset of 50,000,000 customer/user records, generated for developers and builders who need realistic-looking test data without touching any real personal information.

Every value in this dataset is artificially generated. No real people, no scraped data, no real PII. It's built for seeding databases, load-testing APIs, prototyping apps, testing ETL pipelines, and demoing software with data that looks real but isn't.

Schema

Column	Type	Description
`full_name`	string	Synthetic first + last name
`email`	string	Synthetic email address (name-derived)
`street_address`	string	Synthetic street number + name
`city`	string	Synthetic city name
`state`	string	US state abbreviation (2-letter)
`zip_code`	string	5-digit US-style postal code
`phone`	string	US-style phone number, `(NXX) NXX-XXXX` format
`signup_date`	string	ISO date (`YYYY-MM-DD`), spread across ~6 years
`account_status`	string	One of: `active`, `inactive`, `trial`, `suspended`

Account status distribution (approx): active 65%, inactive 15%, trial 12%, suspended 8%.

Format

Apache Parquet, Snappy compression
One file, ~2.8 GB, 50,000,000 rows
Loads cleanly with pandas, polars, DuckDB, PyArrow, or the datasets library

Quick start

import pandas as pd

df = pd.read_parquet("synthetic_users_50M.parquet")
print(df.head())

Or with the datasets library:

from datasets import load_dataset

ds = load_dataset("ziadatalabs/FreeSyntheticCustomerData50M")

Or with DuckDB (great for querying without loading it all into memory):

SELECT account_status, count(*)
FROM 'synthetic_users_50M.parquet'
GROUP BY account_status;

Notes

All data is synthetic and generated programmatically. Any resemblance to real individuals is coincidental.
Emails, addresses, and phone numbers follow realistic formats but are not real, deliverable, or dialable.
This is the first of several free synthetic datasets planned for builders — more types coming.

License & Usage

Released under CC BY-NC 4.0 — free for personal, research, and educational use, with attribution, no commercial use. See the license for details.

Published by Zia Data Labs. We create synthetic data — and we give some of it away free, because good test data shouldn't be hard to find.

Feedback, comments, or requests? Reach us at zia.data.team@protonmail.com