Tag: Analytics

The World's Largest Analytics Networker

1) What prompted you take a career in science, and what has been the reason you stuck to it, and been a success in it ?

I was doing mathematics for fun at a very young age when my friends were interested in sports, cars and movies. When I finished my master, I was approached by one of the professors to pursue a PhD program. It was in statistics (image analysis, bayesian clustering), and I thought that choosing statistics rather than number theory  or numerical analysis would increase my chances of getting a job after presenting my thesis. At that time, my favorite subject was indeed number theory – I was even published in J. of Number Theory. After earning my PhD, I moved to Cambridge, then North Carolina, then the Internet industry – with a very interesting detour into finance and risk management / fraud detection between 2002 and 2005.

2) AnalyticBridge is the world’s largest network for analytic professionals ? What prompted you to build it, what were the critical milestones, and what is your vision for it ?

It is a convergence of multiple factors. The feeling that the startup I was involved with at that time wasn’t doing well, the fact that I had a large network (thanks in part to LinkedIn) and that I discovered Ning.com (while browsing recruiter networks) on February 16th, 2008 – the date AnalyticBridge was born. I decided to create and grow AnalyticBridge very fast, both through networking, quality content, and significant paid advertising. I hope that within 5 years it will be five times bigger in terms of members, and even more profitable

Continue reading “The World's Largest Analytics Networker”

Customized Data Mining Search

Didnt find what you were looking for on this site.Search again on the top 776 sites

 

Try again to this custom engine. As an added amusement do check the Adsense ads (i.e Transport logistics and Hovercraft ad for logistic regression 🙂 )

Note -This remains a non commerical site.

 

var googleSearchIframeName = “cse-search-results”;
var googleSearchFormName = “cse-search-box”;
var googleSearchFrameWidth = 600;
var googleSearchDomain = “www.google.com”;
var googleSearchPath = “/cse”;

 

Modified Ohri Framework

 

Some time back, I had created a framework for data mining through on demand cloud computing. This is the next version- it is free to use for all, with only authorship credit back to me…………..
 
It tries to do away with fixed server ,desktop costs AND fixed software costs in softwares which are used for data mining ,stats and analytics and have huge huge per CPU count annual license fees

 

The modified Ohri Framework tries to mash the following

 

0) HTTPS rather than HTTP

1) Encryption and Compression Software for data transfer (like PGP)

2) Open source stats package like R in cloud computer (like Amazon EC2 or Rightscale  with hadoop)

3) GUI to make it easy to use (like Rattle GUI and PMML Package)

4) A Data Mining Open Source Package (like Rapid Miner or Splunk)

5) RIA Graphics (like Silverlight )

6) Secure Output to cloud computing devices (like Google Docs)

7) Billing or Priced at simple cost plus X % (where simple cost can be like 0.85 cent /per instance hour or more depending on usage and X should not be more than 15 %)

8) Open source sharing of all code to ensure community sandboxing

 

Intention is to remove fixed computing costs of servers and desktops to normal PC’s (Ubuntu Linux ) with (Firefox or IE Explorer ) access to secure data mining on demand .

On tap demand mining to anyone in the world without going for the big license purchases/renewals (software expenses) or big hardware purchases (which become obsolete in 2-3 years).

 

 

SAS Analytics :Google Earth and Lex Jansen’s Site

Google earth stores values into KML files . These are almost like XMl file formats. The zipped versions of the KML file is the KMZ file .(It beats me why Google Wanted to create a zipped file format for KML ,since most KML files are extremely small).

To do any geo-coding analysis with Google Earth, here are two SAS papers from Lex Jansen’s terrific site.

1) 

Put Your Customers on the Map: Integrating SAS/GRAPH and Google Earth
(http://www2.sas.com/proceedings/forum2008/252-2008.pdf)

Daniel Kuiper, Koen Vyverman (SAS Global Forum, 2008-03)

 

and

2) Using SAS and Google Earth to Access and Display Air Pollution Data

(http://www2.sas.com/proceedings/forum2008/253-2008.pdf)
Joshua Drukenbrod, David Mintz (SAS Global Forum, 2008-03)

 

These two papers are great in the way they use Google Earth for geo coding analysis and visual representation. They however require SAS to be licensed with you.

Lex Jansen ‘s site is generally considered the de facto site to search for analytics especially related to SAS.

 

 

 

 

 

 

 

 

 

 

 

 

Analytics through the Browser : Strata

image

Here is an interesting concept of a data browser called Strata by a company called Kirix ( http://www.kirix.com/ ). It promises to connect your online , offfline data and help you perform analytics on it. It has a 30 days trial version . I am currently evaluating and will keep you posted.

This is one more example of analytics moving online ,from packaged software .

The Ohri Framework – Data Mining on Demand

The Ohri Framework tries to create an economic alternative to proprietary data mining softwares by giving more value to the customer and utilizing open source statistical package R , with the GUI Rattle , hosted on a cloud computing environment.

It is based on the following assumptions-

1) R is relatively inefficient in processing bigger file sizes on same desktop configuration as other softwares like SAS.

2) R has a steep learning curve , hence the need for the GUI Rattle .

3) The enhanced need for computing resources for R is best solved using a cloud computing on demand processing environment. This enables R to scale up to whatever processing power it needs. Mainstream data mining softwares charge by CPU count for servers and are much more expensive due to software costs alone.

Continue reading “The Ohri Framework – Data Mining on Demand”