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Quant development: Are you aware of the FIX Protocol and the implications/value of Big Data for the FIX Protocol?

(Last Updated On: January 10, 2012)

Quant development: Are you aware of the FIX Protocol and the implications/value of Big Data for the FIX Protocol?

 

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‘Big data’ is backend analytics; FIX is a front-end protocol. Unless you’ve built to use FIX end-to-end throughout the stack (which is poor, due to lack of internal flexibility to pivot on business requirements and changing needs) then they should be orthogonal due to execution space.

I’m curious what use-case you’re thinking of in which ‘big data’ would have have an impact on the protocol itself.

Maybe a sixth option to your poll: “There is no impact.” 🙂

 

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Not exactly.

I think you’re reading something in to Carl’s question.
(Maybe I’m just being obtuse and taking it at face value.)

Yes, FIX and Hadoop are Orthogonal because as you point out FIX is a protocol, Hadoop is an environment for doing parallel processing. (Note I wouldn’t say that Hadoop is just for back end processing. Companies like HStreaming would beg to differ.)

I would have interpreted the  question to be asking if you’re aware of the value in doing data mining / analytic research on FIX data?

Again, I have to say maybe I misinterpret what is being said? Who knows? That’s what makes these discussions fun. 🙂

 

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I am only bring the thoughts together of Big Data and FIX in the realms of the bringing together of FIX data in the BIG DATA world. lets not forget that the Billions ‘s of millions of msgs that FIX produce per day can be compared / visualized etc agasint other data.

I am only opening a topic of conversation, hence the poll rather then a fully-fledged drill-down discussion (esle I’d start talkign about SIFT msgs, BIC Codes,a nd Big data, btu frmo a BI perspective, ro even a MDM perspective against other unstructed data)

Thanks for the comments though.

Feel free to take part in the poll.

My interest is to see awareness, later of course we can get to specifics.

 

 

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