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Shawn Hessinger

CRM & Marketing Top Fields for Data Miners

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SethBreedlove
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Data Doctor
Re: Top Fields for Data Miners
SethBreedlove   11/22/2011 3:48:28 PM
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@ Dataguy - Thanks, you make some really great points.  There really is a great divide in the work force. 

dataguy
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Prospector
Re: Top Fields for Data Miners
dataguy   11/22/2011 3:35:33 PM
@Seth: from my experience, dirty and difficult data is a problem because it is difficult to convince stakeholders of the importance of cleaning it up. So we either publish untrustworthy results quickly, or we anger those who pay our salaries by taking too long. Tools are good, but this is time consuming and expensive and not always seen as valuable.

On the other hand, explaining the work effectively includes the above conundrum but goes far beyond it. There is a tremendously deep and wide set of significantly complex science involved in data analytics, but explaining this to anyone at all is challenging.  It is hard enough to find qualified people to do the work competently. If you want them to communicate effectively also, you're reducing your talent pool even further.

SethBreedlove
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Data Doctor
Re: Top Fields for Data Miners
SethBreedlove   11/22/2011 3:07:50 PM
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I have definitely seen an increase in the requirments for analytics in many job postings and like the chart says, in marketing. Like others, I am surprised that CRM/marketing is number one, but I guess that makes sense as it's more profitible to retain and market to a current customer. 

I would like to know more about the reasons behind "The biggest challenges for data miners remain dirty and difficult-to-access data, as well as the ability to explain their work to others effectively."   Is it the lack of tools or the lack of understanding? 

Pierre DeBois
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Top Field for Data Miners - the CRM/Marketing set
Pierre DeBois   11/13/2011 7:00:09 AM
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One thought about this - I can see how data miners would be mostly into the CRM/Marketing segment. It's easily identifiable by a manager to budget with so much interest in targeting customers better.  

Also there are more CRMs incorporating social media, so certainly there is a need to manage highly continuous information.

 

 

Pierre DeBois
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Blogger
Re: Top Fields for Data Miners
Pierre DeBois   11/13/2011 6:55:40 AM
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Shawn,

What does internet-based mean in the survey? Are they cloud services which are non marketing related? I was just surprised by the CRM/Marketing distiction from internet-based.

 

Thanks for any insight. 

Shawn Hessinger
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Blogger
Re: Academics is #3?
Shawn Hessinger   11/10/2011 11:41:40 PM
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Hi Cordell,

Yes, especially insurance given the potential importance of data mining in risk assessment. But I have to honestly say that I was also surprised by the distance that medical and Internet are behind, two fields where it is obvious to see the benefits of data mining.

Louis Watson
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Re: Data Mining: Real Challenges Ahead
Louis Watson   11/10/2011 11:38:27 PM
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Cordell, Thanks for the clarification of standard practice on credit scores. I see your point that it is not the variable in itself that is the issue, it whether is has any significant meaning to the question(s) at hand.

Interesting insight.


Cordell
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Academics is #3?
Cordell   11/10/2011 10:33:31 PM
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Surprised to see academics ahead of insurance and telecom.

Cordell
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Re: Top Fields for Data Miners
Cordell   11/10/2011 10:30:38 PM
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@dataguy.   Certainly terms get jumbled a lot.  I recall talking to a lot of people about "analytics" which took to mean predictive analytics and they were typically talking about reporting or BI.  Some really confusing conversations!  Nevermind people passing off analytics that aren't.  See our discussion on sentiment analysis that's just keyword search.

Cordell
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Blogger
Re: Data Mining: Real Challenges Ahead
Cordell   11/10/2011 10:21:46 PM
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@louis.  I can confirm that most credit scoring models don't have more than about 15 characteristics though they may start with hundreds.  It's not the management of variables that's the problem it's that after about 15, new variables add little to the model.  Of course credit scores have been around for a long time and over the years the strongest variables are fairly well known so there's a good starting point already.

I totally agree about communication.  If findings can't be communicated accurately then what's the point!  This is an ongoing skill set deficit.  Tough to find analysts that are good communicators.  It's a stereotype I know but it seem to be directionally correct at least.

 

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