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Data at work


why bi
Statistics
Bi
Analytics
forecasting



Statistics is commonly misunderstood, as it can be:
At the glossary references to meaning of words are collected Analytics - mathematics

All references off abuse and (mis)intrepretation of statisics at the dedicates page: Abuse of statistics




working on this I´m working mostly on other pages at this moment (aug 2012).
Found this was subject to do as dedicated subject. Links and parapgraph´s will be moved to here.

For the most time this page will be a mesh-up. As soon I see the hit-ratio will grow I will do a clean-up.



Industry





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Weather





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Robotica





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Health





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Social



Analysing social sentiment:

Analysing social sentiment:

Analysing social sentiment:

Analyzing relationships friends:



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Marketing



complex
Big data analyses
how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did Even if you’ve fully stalked the person on Facebook and Google beforehand, pretend like you know less than you do so as not to creep the person out.


Don&cutet Look Now, There&cutes a GPS Tracker in Your Kit-Kat Bar Customers buying Kit-Kat bars in the United Kingdom could be unwrapping a 21st-century version of Willy Wonka’s Golden Ticket–a GPS unit the candy-maker will use to find them, apprehend them and give them a prize.


Personality Traits as Chronic Motivations Get Around the Confabulator The point here is that sometimes people can report their motivations (e.g., eco-consciousness, supporting local businesses), but sometimes they can’t (e.g., desire for uniqueness), and sometimes they report false motives (e.g., nostalgia).




marketing of the big supermarket: Walmart (founded 1962)
Walmart Makes Big Data Part of Its DNA horicky.blogspot.nl/2011/09





believe
Correlation variable elimination
Building models is requiring good variable candidates.
When to use mutual information correlation based feature selection (simaforce)


choose
Recommendation engine, collaborative filtering, market basket
A " Recommender_system " (wiki) is something that will give predictive advices.
The best known innovator of this is Amazon . Opening up with offerings related to your interest.

Every business has history on his customers. It can be used to build a filtering analyses.
On interenet many footprints are left behind. It can be used to build a filtering anlayses.
Public available information may be related to the current user (if known) It can be used to build a filtering anlayses.



Sample of a nice written description of the theory: recommendation-engine horicky.blogspot.nl/2011/09
It is mentioning some statistical functions that are possible to be used. Pearson_product-moment_correlation_coefficient (wiki) and Jaccard_index (wiki).

A worked out sample advicing education: ectel2007-romero (wwwis.win.tue.nl)  

Having the hyping tools to be used like hadoop, it is possible to solve like: part-1 , part-2 recommendation-engine-powered-by-hadoop pkghosh.wordpress.com/2010  

Churn - Customer segmentation -rtdm





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Insurance





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Banking





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Income - Spend



Metrics - Data

Investment in education

List of universities and school programs:



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© 2012 J.A.Karman (21 apr 2012)