Panel discussion on data science in business

While the term "data science" is relatively new, and maybe overhyped by some, many of its methods have seasoned and sound foundations in statistics, computer science and their various related fields (e.g. data visualization, machine learning, databases, distributed computing etc.). While there is perhaps yet no general agreement on what data science exactly encompasses (maybe ultimately it is "just" a multitude of statistical and computational methods for data analysis put in a modern context), it is generally agreed that these methods are very useful for many businesses in utilizing their untapped data for decision making, optimizing processes, and ultimately improving their bottom line.

However, due to the complexity of the methods, the skills required, and many methodological, technical and organizational challenges, it is not trivial to obtain the best results in a given business setting. In this meetup we'll have a panel of 6 seasoned professionals in the data analytical field (and all of them advanced R users and previously speakers at this group), who will discuss various aspects of the challenges in making data science and R achieve its maximum potential in companies.

Panelists: Avram Aelony, Eric Kostello, Yasmin Lucero, Szilard Pafka, Ryan Rosario, Oliver Will

Timeline:

- 6:15pm pizza arrives and networking

- 7:00pm panel starts promptly

Please arrive by 6:55pm the latest

Please RSVP as places are limited.

Venue: Adconion Media Group (3301 Exposition Blvd, Santa Monica). They will kindly validate parking and provide pizza and drinks (big thanks to Mikhail and AMG for that and for providing the place).

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  • e

    Not focused. got carried away by discussions on defining data scientist...social science.. etc etc

    January 25, 2013

    • - Szilard Pafka -

      Indeed, that was a part of it, but from the other (more complete) feedbacks it looks like overall it was interesting and many are looking forward for a 2nd round. Thanks for those providing detailed feedback, so that we can incorporate that into the next round.

      January 27, 2013

    • Daniel G.

      In my opinion, the panel discussion was very well focused and I enjoyed the early comments about what a data scientist does. I fully support a follow-up panel discussion to cover even more territory.

      January 27, 2013

  • Divya P.

    Panel was too long

    January 25, 2013

    • - Szilard Pafka -

      i rather think it was short ;) so was this "feedback"

      January 27, 2013

  • Rick L.

    I always enjoy the R Meetups and especially like discovering new packages and tools that I can integrate into my own workflow. (e.g. knitR, ggmap, shiny, node.js, redis, ec2, etc.)

    Last night was the first panel discussion Meetup I've attended. While I did enjoy it, I felt a lot of time was spent discussing subjective topics (especially labels - 'PhD', 'data scientist', etc.). I may be in the minority here, but my suggestion for future panel discussions would be to only allow questions at the end to prevent the discussions from getting sidetracked.

    That said, I am looking forward to future R Meetups.

    January 25, 2013

    • Tim Triche, J.

      It is surprising just how much "soft" scientists (scare quotes intentional) have to offer for those of us who have come up from an engineering, ops, or "hard" science background. It's possible to take the models too far, but the process of building a model for something you can't see, touch, or directly measure has much to inform the business case. Because that, in so many words, is the value proposition.

      The emphasis from the "social scientists" (more scare quotes, because every last one of the panelists had a hard quantitative background) on communication was eye-opening. To paraphrase Avram, the difference between the right word and the almost-right word is ~100k/year.

      January 25, 2013

    • rex f.

      as a soft scientist, i spent eight years in biomedical research. my specialty was in stem cells and fluorescent proteins as a biologist. during my training many mathematical principles were applied in the form of statistical analysis (gene expression, etc) and some recombinant gene technology (designing nucleic acid primers for gene amplification) that is not a hard science, but requires abstract thinking. not to mention optics/physics regarding light/laser wavelengths that are necessary for 'exciting' fluorescent proteins... it was very motivating that from this background i have the chance to contribute as an analyst. i delivered my phd defense on 12/27 in new england and just recently moved back, this was my first R group meeting, and i am now programming; and thank you for the discussion panel. as s result, i now have a much more solid understanding how my spss background may contribute to learning R.

      January 25, 2013

  • Yasmin L.

    Great.

    January 25, 2013

  • Bill L.

    Excellent meeting and one that definitely needs a follow up.

    I agree with others that there needs to be a strong moderator who will keep discussions on track.

    January 25, 2013

  • Oliver

    Good

    January 25, 2013

  • Yasmin L.

    Do we have any trained moderators in the group who would like volunteer their services?

    January 25, 2013

  • Shannon C.

    Thank you, Szilard, for organizing and thank you to all who made the Meetup happen. I echo Tim's comments. I enjoyed hearing the panel's views about data access. I wanted to hear about data cleaning and data prep---procedures, tricks, anecdotal stories. Also I'm curious as to what % of the workload it is for the panelists, realizing that it varies by project. I'm always interested in hearing about packages that data people find handy (aside from the commonly used ones). I was also wondering if the panelists do only numerical analysis or if they are doing text/sentiment analysis as well and if that has changed in recent years. Once again, thanks to all who put the Meetup together and thank you Adconion for sponsoring.

    January 25, 2013

  • Tim Triche, J.

    Good, but even jewels can stand to be polished

    January 25, 2013

  • Andrew D.

    Interesting social-science-of-data-analysis-in-business meeting. It's good to have an occasional alternate to the usual very fine technical talks. I am still looking forward to a de-bunking of the Big Data hype, and a de-bunking of various tools' capabilities, wherever appropriate.

    January 25, 2013

  • - Szilard Pafka -

    Please leave feedback. We'd like to continue on this and have a 2nd round in a few months (likely in May).

    January 24, 2013

    • Tim Triche, J.

      Last night was great. Thank you, Szilard, for organizing a round table with such diverse panelists! A follow up could be even better, with a bit of prep. I'd suggest:

      1) Assemble a list of questions from RSVP'ed attendees. Why are they coming, what do they want to find out? It focuses the discussion, though it need not constrain it.

      2) Have a moderator. Someone to cut off the mike when people ramble. There were some real pearls in last night's discussion, but there was also a lot of back-slapping BS, which isn't respectful of the audience's time and interests.

      3) I believe people are desperate for clarity as to what a "data scientist" is, does, and can offer in terms of value, and when a company actually needs one. It helps avoid a market where talented people end up in jobs they hate, working for people under whom they cannot add value. Again, thanks much Szilard, Rob, and all the participants (especially Avram). I learned quite a bit last night.

      January 25, 2013

  • Daniel G.

    What a great evening. This Meetup was superb. Great vibe, plenty of energy and so much brain food!

    January 24, 2013

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