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SAP: Advanced Analytics Not Just For PhDs Anymore
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brunoaziza
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brunoaziza,
User Rank: Apprentice
12/10/2013 | 11:32:11 PM
Re: A Deeper Level of Analytics
Great article Doug and indeed great points made via your comments.  Running serious math is important and it's a sophisticated discipline.  However, the era where users had to go through a huge learning curve because the software and methodoloiges of the past were cumbersome, is over.  What we are talking about now is not so much about just 'data democracy' but about bringing forth tools that can help all users interact with data with more ease.  The new approaches available to data scientists promote collaboration and openess as opposed the old paradigm, where a few could code their way through problems in isolation.  The market is ready for it too: new generations coming into the workforce are more 'data-literate' than their parents. The data sources we now have access to are more plentiful and diverse.  The economics and expectations around enterprise software have changed.  It's time to harness the potential of Data Science and spread it across companies and departmnents so more of them can become predictive enterprises.

Analytically Yours,

Bruno Aziza, Alpine Data Labs

 
D. Henschen
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D. Henschen,
User Rank: Author
12/9/2013 | 10:37:16 PM
Re: A Deeper Level of Analytics
The point is that doing predictive analysis should not be like brain surgery. Earlier this year Forrester pointed to progress being made by a number of vendors to make anlytics easier, and it encouraged the rest of the industry to follow suit. Simplified data-access, easier process workflows and automated modeling and scoring tools are among the innovations that have been applied to the problem. In short, the software can be smarter, eliminating some of the labor intensive and iterative steps required by earlier generations of software.   
cbabcock
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cbabcock,
User Rank: Author
12/9/2013 | 5:24:34 PM
It is rocket science
It is rocket science. We can ease the pain of coming up with business intelligence and predictive analytics by building ease of use front ends for specific areas. And we can keep making it easier to visualize what's in the data or work with models using pre-defined data. But coming up with the specific intelligence you're looking for from data sets that are unique to you, that's still a challenge. It takes someone who can write a custom algorithm.
RobPreston
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RobPreston,
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12/9/2013 | 3:35:32 PM
Re: A Deeper Level of Analytics
Doug, we've been hearing about "analytics for the masses" for at least a few years now. What's the biggest obstacle? Is the software still too complicated? Will the needed expertise always be too advanced and specialized (we don't hear about the need for brain surgery for the masses)?
D. Henschen
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D. Henschen,
User Rank: Author
12/9/2013 | 3:22:24 PM
A Deeper Level of Analytics
Founded in 1988, KXEN has been at the analytics game for a long time. SAP, on the hand, has done advanced analytics for only about five years. The original product developed by BusinessObjects was based on technology licensed from SPSS (before that company was acquired by IBM). The SAP Predictive Analysis module introduced about 18 months ago replaced the SPSS code base with new tools and added an extensive library of analytics based on the R statistical language. I've talked to a few BusinessObjects customers that are experimenting with Predictive Analysis, but KXEN has more than 500 customers concentrated in financial services, telecom, and retailing.

So what's first on your list: helping advanced users automate and be more productive or exposing predictive modeling capabilities to business users?


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