How to find thousands of company names? [closed]

Question

How can I find or generate thousands of company names for testing and demo purposes? (Address, phone number, and related information would be nice too.)

I've got a system I'm building which includes business contact information. Pretty common no doubt.

My test/demo database currently has randomly generated individual's names loaded (thanks to a handy IRS spreadsheet I found). This has worked great for internal testing and review purposes, but it looks really odd when shown to prospective customers.

I've tried various online public information sources (e.g. EDGAR, and county based property records searches), but these all require me to manually stitch together the results in blocks of 50 names or so at a time. I could do this, but was really hoping for a search service or data store out there that had this type of information readily searchable and retrievable in very large batches.

Pasadena

Dummy data is a nice thing, because you don't want to use real data. Good question. – Pears

The "handy IRS spreadsheet I found" made me take pause. I'm sure it's innocent, but I'm not sure why (washingtonpost.com/wp-dyn/content/article/2007/04/04/…) I'm a bit nervous (schneier.com/blog/archives/2007/01/kansas_city_los.html) – Cicatrix

Hmm, yea, I should have explained further :) The spreadsheet (lost the link) had one column with thousands of first names and another column with thousands of last names. And there was a macro which scrambled 'em all up. No other sensitive data. – Pasadena

This question would be on-topic at opendata.stackexchange.com – Mundford

Answer 1

I use Fake Name generator:

What can I use the Fake Name Generator identities for?

Thousands of individuals, companies, and government organizations have found useful and creative things to do with the Fake Name Generator. Here are a few examples:

• Quality test data can be hard to come by, especially with laws (such as HIPAA) preventing use of real data. Read more on the dangers of testing with real data.
• Many websites, such message boards, are poorly designed, making it difficult for visitors from foreign countries to sign up for accounts. Using fake information, you can easily fill out the sign up forms and log in to the site.
• Use fake information when filling out forms to avoid giving out personal information.
• Generate a false identity to use as your pseudonym on the internet. This allows you to keep your real life and your internet life separate.
• Get ideas for names to use for characters in a book or story.
• Generated credit cards can be used to test basic client-/server-side validation techniques without accidentally processing a real card.
• Generated national identity numbers can be used to test basic client-/server-side validation techniques without risking disclosure of real information...

Prebo

Wow, that's an incredibly awesome service. Thanks for the link. Only problem for this particular purpose is that it's individual names. – Pasadena

Can this be used to make a big ol' list, or just one at a time? I reckon some enterprising automater would figure out a way to use WatiN or some such thing to extract a bunch of names robotically. Let me know how that works for you. – Pears

true - but i think they'll do custom work for free/cheap – Prebo

They offer on that site to generate 1 million records in the format of your choice for $25. That's cheap for a ton of data. – Pasadena

Very cool. By the way, you can get all the free names you want for free, but only 120,000 at a time (40,000 per free request max * 3 requests in the queue max). – Fantasia

Snap, that's way cheaper than trying to 'robot' the info. I'm going to send that URL to my dev peeps. – Pears

Answer 2

A pretty good generator is: generatedata.

It's very customizable: you can generate names, streets, telephone numbers, a random entry from a specified list.

You can export the generated data in different formats like: SQL, HTML, Excel, XML and CSV.

Carbonation

Answer 3

You could scrape a public source like Wikipedia for names, or you could just grab random (non-offensive, of course) nouns from your dictionary of choice (/usr/share/dict/words, etc.) and append "Company", "Corporation", "LTD" at random.

Beckner

that's a rather clever idea (the /usr/share/dict/words thing) ... I've used that for crossword puzzle solving, but hadn't thought of it for company names – Prebo

Answer 4

I personally STRONGLY recommend against using ACTUAL data of any form for testing/demoing an application.

I have had to go in too many times and pick up the pieces when real e-mail addresses were used and emails accidentally went out to all kinds of customers.

I would use something like the tools from RedGate to add data, make it dummy data, real data is too risky, at least in my opinion.

Tautology

Agreed. I'm not going to be using the email addresses for these purposes and can see where that could bite you. I was interested to see that the FakeNameGenerator.com guys also include an email address that points back to them for testing purposes. – Pasadena

Answer 5

I would suggest having a "random character" generator that strings together "company name" "companytype" and so forth. This will minimize the chance of actually displaying a real company's name.

Also, check out the Ipsum Lorum generators; they might have some tips.

Arhat

Answer 6

If you are simply looking to generate names, I would use one of the two above options. If you are looking for more complex data, Redgate makes a SQL data generator. I have never used this program, I simply know of its existence.

Anishaaniso

Answer 7

A great tool for programmatically generating fake names (both company and individual) is Faker. Basically the same implementation can be found in Python, Ruby, and Perl. I'm not sure where it originated, but definitely worth checking out if you're comfortable with any of those programming languages. It can also generate fake names from languages other than English.

Links:

• PyFaker
• Ruby's Faker
• Perl's Data::Faker

Here's an excerpt from PyFaker's Readme, just to give you a flavor of it:

In [1]: from pyfaker import Fake

In [2]: fake = Fake(lang_code='en')

In [3]: fake.Address.street_address()
Out[3]: u'72449 Ward Shore'

In [4]: fake.Address.street_address()
Out[4]: u'7954 Waelchi Mall'

In [5]: fake.Company.bs()
Out[5]: u'whiteboard visionary markets'

In [6]: fake.Company.bs()
Out[6]: u'exploit innovative paradigms'

In [7]: fake.Name.name()
Out[7]: u'Aaliyah Bauch'

In [8]: fake.Name.name()
Out[8]: u"Chad O'Keefe"

Locus