State of Data #72

#analysisThe most comprehensive guide to Mobile Statistics ever 

A trip to the darker sideAnalyzing Hackers – what do they talk about the most vs. real life threats, and how precious data is traded at ‘black market’ (PDF) 


#architecture  
Peter Norvig on how AI is revolutionizing search

Google Voice Search relies on 230 billion real world search queries to learn all the different ways that people articulate given words. So people no longer need to train their speech recognition for their own voice, as Google has enough real world examples to make that step unnecessary.

Finally, the words are strung together into a language model, which tells you which words are most likely to come after another word. There might be a soundwave that sounds like either “city” or “silly”, but if it follows the words “New York…” then the language model would tell us that “city” is more likely. 

#big_dataMcKinsey asks ‘Are you ready for the era of Big Data’ with five questions (Jeopardy think music begins here) – 

1.      What happens in a world of radical transparency, with data widely available? 
2.   If you could test all of your decisions, how would that change the way you compete?   
3.     How would your business change if you used big data for widespread, real-time customization?
4.    How can big data augment or even replace management? 
5.     Could you create a new business model based on data?

#conferenceAI Challenge 2011 –“watch your ant colony fight for domination against colonies created by other people from around the world


#Data_Science –  
What happens when your business is “Statistics as a Platform 


#DBMS
Want a database to play dice and just pick just a random plan (NOT the best plan) for a query? There’s a hidden parameter for that.


#idea 3 Experts offer ideas on ‘Competing through Data’. Insights – 

·   Most great revolutions in science are preceded by revolutions in measurement 

·   one-standard-deviation increase toward data and analytics was correlated with about a 5 to 6 percent improvement in productivity and a slightly larger increase in profitability 

·  I can have all the data I want to have—but I still have to communicate it to our players.   


#learning
‘Signs that you’re a Bad Programmer’. Best insight –

Inability to think in sets

Transitioning from imperative programming to functional and  declarative programming will immediately require you to think about operating
on sets of data as your primitive, not scalar values.

Remedies

Funny enough, visualizing a card dealer cutting a deck of cards and interleaving the two stacks together by flipping through them with his thumbs can jolt the mind
into thinking about sets and how you can operate on them in bulk. 


#visualization
Want a handy Baseball correlation ellipse or Image Scatter Plot (like how flu spreads) to communicate data – R Graph Gallery is there to help.

#etc 


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About Nilendu Misra
I love to learn, create and coach. Things that I do well are - Communicating ideas - verbally or through words and diagrams; Problem Solving - Logical or Abstract; Very Large Scale Systems; think about 'Frighteningly Simple' approach first. Things that I intend to do better are - Establishing Stringent Process; Exchanging Tough Feedback; Keeping up with my reading or To-Do list to be able to completely relax.

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