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How to Extract and Analyze Data from Wikipedia Using SQL

mixnode.com

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Re: How to Extract and Analyze Data from Wikipedia Using SQL

#4

Post by enjayz »

donkoz_ab wrote: post #2

I joined the beta list last week. Any rough estimate as to how long till I get my invite?

Hi there, co-founder here. I'm really sorry about the wait and inconvenience. We send invitations in batches and there are a lot of people on the waitlist. In the meantime, you can contact me directly if you have any questions: nj@mixnode.com

Re: How to Extract and Analyze Data from Wikipedia Using SQL

#7

Post by sixdimensional »

I couldn't see from the site - does this have a corresponding ODBC/JDBC driver implementation?

I can imagine a LOT of people wanting to blend the resulting data with other datasets, or even across results from the service itself. For example, could do that using Dremio, or commercial tools like Tableau, etc.

This reminds me faintly of what triple stores, RDF and SparQL were supposed to accomplish a la the Linked Data initiative [1]. But you know... with SQL instead.. like maybe how they should have started?

Awesome use of SQL here :)

I bet you could also do something interesting doing NLP to SQL here as well.

Intrigued to see where this project goes. Great idea!

[1] http://linkeddata.org

Re: How to Extract and Analyze Data from Wikipedia Using SQL

#8

Post by enjayz »

sixdimensional wrote: post #7

I couldn't see from the site - does this have a corresponding ODBC/JDBC driver implementation? I can imagine a LOT of people wanting to blend the resulting data with other datasets, or even across results from the service itself. For example, could do that using Dremio, or commercial tools like Tableau, etc. This reminds me faintly of what triple stores, RDF and SparQL were supposed to accomplish a la the Linked Data…

Thank you so much :) Mixnode will come with a lot of integration points/SDKs. If you need a specific integration you can send us a feature request at hi@mixnode.com, will be more than happy to look into it.
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