I had to chime in about the buzz around the new search engine -- or more accurately, "computation engine", as they classive themselves -- Wolfram|Alpha.

When WolframAlpha doesn't understand your query (e.g., big4 accounting firms), it says "Wolfram|Alpha isn't sure what to do with your input." But it may also suggest "Related inputs to try:" or "did you mean": and, in this case, a hyperlink to big4 accounting which it interprets as (nice that it also displays its interpretation) "4 biggest business services" and showed top companies in that space by market capitalization.

You can better think how to use it by noting its "tips for good results" link which says:

• Wolfram|Alpha answers specific questions rather than explaining general topics (enter "2 cups of sugar", not "nutrition information")
• You can only get answers about objective facts: Try "highest mountain", not "most beautiful painting"
• Only what is known is known to Wolfram|Alpha: Ask "how many men in Mauritania", not "how many monsters in Loch Ness"
• Only public information is available: Request "GDP of France", not "home phone of Michael Jordan"
• Don't use long complete sentences; just enter minimum words
• Try different words or notations
• Use whole words instead of abbreviations
• Check your spelling

Amybeth Hale's post said "if you're looking for current events or assistance with your sourcing efforts, you're going to be disappointed" though she did illustrate how it runs side-by-side comparisons of individual companies. Ryan Leary's post argues that Wolfram|Alpha is useful for salary, demographic, and industry growth data.

But a recruiting researcher's natural tendency, of course, is to look for people information. You can search by names, but if it's not a famous person, you get no results. The examples under "People and History" won't impress sourcers. It provides gender and number of US births for a given name but it can't handle names traditionally associated with other countries (e.g., no data for Dieter, Sanjay, etc.).

"Organizations" data is straightforward for individual companies, but don't expect it to find any professional organizations/associations, whether you indicate by industry or even if you know the particular name of one.

How it handles (some) job titles and industry keywords is interesting. The default treats a job title as an occupation with Ryan's aforementioned skew, but it gives you the option to treat it "as a word", which yields different kinds of results. Ditto if you type a term like software which the engine may think is an individual company but you'll get more useful results from its alternate keywords list if you click the "word" treatment.

Even inputting technical terms you don't understand isn't going to yield much (e.g., computer science or engineering).

So I concur with my recruiting blogging colleagues and won't be giving up major search engines anytime soon. But Wolfram admits they're not perfect, so feel free to suggest a new data source or any other feedback.