Meta S. Brown

Grow Your Own Analytics Talent

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Louis Watson
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Analytics Talent and Unreasonable Expectations
Louis Watson   11/29/2012 3:16:47 AM
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Wonderful, spot on message Meta regarding fostering your own internal talent.  I so enjoyed reading your take on headhunters parroting the demands that even most employers do not truly understand.

I have seen these listings and while I don't mind studying towards something, what most companies are asking for is often unrealistic.  Almost to the point of being absurd.   

So while the position(s) go unfilled - these companies can continue to do apparently what they do best - hold unreasonable expectations.

And if they do find this person with it all - are they prepared to adequately compensate ?  

And I love your true life example of a secretary who made it big !  Good for her !

Hospice_Houngbo
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Prospector
Re: What Wal-Mart does...
Hospice_Houngbo   11/28/2012 5:16:58 PM
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Hi Beth,

 You are right about the risk of limiting creative thinking if we limit "what can be done with the data". But the source of the data and the features of its different instances should allow us to limit the scope of our predictive model. But it is true that ruling out only the obvious "can'ts" is the right thing to do.

BethSchultz
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Blogger
Re: What Wal-Mart does...
BethSchultz   11/28/2012 12:48:56 PM
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Hospice -- I can see some danger in asking "What can't we do with the data?" though -- in that it might limit creative thinking or innovative approaches to modeling (unless you're talking about ruling out the more obvious "can'ts" but not creating too many limitations?).

BethSchultz
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Blogger
Re: What Wal-Mart does...
BethSchultz   11/28/2012 12:46:16 PM
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I love it, Peter! I can see it scrawled across whiteboards in student classrooms, too. It's a great reminder for folks at any level. Thanks for sharing the pic!

Peter Mancini
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Prospector
Re: What Wal-Mart does...
Peter Mancini   11/28/2012 10:36:05 AM
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I love that graphic. It's an excellent illustration. The defense against torturing data is to truely understand the scientific method and the role of experimentation in numerical analysis. Further, understanding the inadequacies of the data you are working with is important in understanding what you can expect to get from it.

That quote went up on my white board (well, 1 of 3!) a few days ago. I guess there is something viral about it as I've seen it now several times in the last week. I placed it as a warning to myself and others. Tread carefully and learn how to respect the analytical process.



Hospice_Houngbo
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Prospector
Re: What Wal-Mart does...
Hospice_Houngbo   11/27/2012 11:53:41 PM
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Thanks for sharing. I think we should start by the asking the question: what can we really do with the data and what can't we do with it? We need to answer that question before trying to build any predictive model with the data we collect.

BethSchultz
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Blogger
Re: What Wal-Mart does...
BethSchultz   11/27/2012 8:52:34 PM
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Meta, I would agree there's danger in thinking that there's magic in the tools -- especially those delivering visualizations. It's too easy to think the data is good because it LOOKS good! You've got to understand what it you need and what the data is telling you.

BethSchultz
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Blogger
Re: Home grown
BethSchultz   11/27/2012 8:48:19 PM
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Great story Meta. Thanks for sharing!

BethSchultz
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Blogger
Re: Home grown
BethSchultz   11/27/2012 8:45:59 PM
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Peter, sounds like you've got a great work environment!

BethSchultz
User Rank
Blogger
Re: What Wal-Mart does...
BethSchultz   11/27/2012 8:32:05 PM
@Peter Mancini, funny you should mention this quote. I heard it just myself a week or so ago, from Mike Swinson, an EVP at TrueCar, in a presentation on predictive modeling he delivered at IE's Predictive Analytics Innovation Summit in Chicago. I just wrote about his presentation today: Ask & Ask Again: Questions Matter in Modeling. I like the imagery he used in his slide presentation:

 



 

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