Data Intelligence, Business Analytics
New highway toll system poorly designed due to lack of analytic thinking
As of yesterday, a toll system is in place for drivers crossing the I-520 bridge, linking Seattle to Redmond, where the big Microsoft campus is located. It is claimed to be the most modern toll system in US, and drivers don't need to stop to cross the bridge, there's actually no toll booths, no human beings to process your payment.…
ContinueAdded by Titus on December 30, 2011 at 5:00pm — No Comments
Data mining without prior assumptions | MIT
The information age is also the age of information overload. Companies, governments, researchers and private citizens are accumulating digital data at an unprecedented rate, and amid all those quintillions of bytes could be the answers to questions of vital human interest: What environmental conditions contribute most to disease outbreaks? What sociopolitical factors contribute most to educational success? What player statistics best predict a baseball team’s win-loss…
ContinueAdded by Jean-Paul Rasson on December 28, 2011 at 11:30am — No Comments
Using Visual Analysis to Detect Call Center and BPO Fraud
Threats within these industries range…
Added by Andrew Marane on December 28, 2011 at 8:30am — No Comments
More about retail analytics
I lived in California a while back, and have experienced a few instances where large companies headquartered e.g. in Minneapolis, were selling products in all their stores nationwide as if everybody in US had the same weather, seasons and body size.
In particular, some stores (maybe Target - I don't remember) that sell garden tables did not have any product available in late February, although late February in much of California is a great time to remodel your garden.
Also,…
ContinueAdded by Mirko Krivanek on December 26, 2011 at 9:00pm — No Comments
Get prediction intervals for your forecasts, with this easy to apply statistical model
In the words of Dr. Chris Chatfield: “Predictions are often given as point forecasts with no guidance as to their likely accuracy (and perhaps even with an unreasonable high number of significant digits implying spurious accuracy!)”.
Our paper sets forth a synergy of existing statistical theories to obtain a clear-cut model for calculating forecasts with prediction intervals, named the…
ContinueAdded by MARTIN VAN WUNNIK on December 26, 2011 at 3:39pm — No Comments
Google acknowledges that its algorithms don't work with the keyword "Jew"
The message below is from Google, you can read the original version at www.google.com/explanation.html.
If you recently used Google to search for the word “Jew,” you may have seen results that were very disturbing. We assure you that the views expressed by the sites in your results are not in any way endorsed by Google. We’d like to explain why you’re seeing these results when you conduct this search.
A site’s…
ContinueAdded by Marcel Remon on December 26, 2011 at 12:30pm — 1 Comment
Big Data Analytics
Big data i
s the new buzzword within the data warehousing and business analytics community.
Added by Sandeep Raut on December 26, 2011 at 10:03am — No Comments
How to build simple, accurate, data-driven, model-free confidence intervals
If observations from a specific experiment (for instance, scores computed on 10 million credit card transactions) are assigned a random bin ID (labeled 1, ··· ,k), then you can easily build a confidence interval for any proportion or score computed on these k random bins, using the Analyticridge…
ContinueAdded by Vincent Granville on December 25, 2011 at 8:00pm — 5 Comments
How could Amazon increase sales by redefining relevancy?
By improving its search and relevancy engines, to include item price as a main factor. The type of optimization and ROI boosting described below applies to all digital catalogs. Here we focus on books.…
ContinueAdded by Vincent Granville on December 25, 2011 at 5:00pm — 1 Comment
Sales forecasts: how to improve accuracy while simplifying models?
The solution is simple: leverage external data, and simplify your predictive model.

Back in 2000 I was working with GE's analytic team to improve sales forecasts for NBC Internet, a web portal owned by NBC. The sales / finance…
ContinueAdded by Vincent Granville on December 24, 2011 at 9:00pm — 3 Comments
Real Life Example of Text Mining to Detect Fraudulent Buyers
The credit card transaction described here in details is a real example of a fraudulent transaction performed by organized criminals, undetected by all financial institutions involved, and very easy to detect with simple text mining techniques.

It was not caught by any of the financial…
ContinueAdded by Vincent Granville on December 21, 2011 at 5:00pm — 1 Comment
IBM Tech Growth Predictions: Energy, Biometrics, Mind Reading, Mobile, Junk Mail | ABC News
Added by Vincent Granville on December 21, 2011 at 1:08pm — No Comments
MINE: Detecting novel associations in large data sets
Added by Vincent Granville on December 20, 2011 at 1:12pm — No Comments
Analytic professionals: are we detailed-oriented or do we think "big picture", or both?
Hiring managers always assumed that I was a very detailed-oriented person. It turns out that this is not the case: I'm certainly a very analytic person, yet I always think "big picture", and everybody who knows me well would say that I am everything but detail-oriented.…

Added by Vincent Granville on December 19, 2011 at 4:30pm — 4 Comments
Full employment through inefficiency?
According to the recent landmark McKinsey Big Data study, by 2018 one in two US jobs requiring deep analytical skills will go unfilled, and there will also be an under-served demand for 1.5 million business managers and analysts “who can ask the right questions and consume the results of the analysis of big data effectively.”
McKinsey and others see it…
ContinueAdded by Tim Negris on December 19, 2011 at 12:00pm — 4 Comments
Apply for the Innovation in Analytics Award
Added by Vincent Granville on December 15, 2011 at 7:29pm — No Comments
Great Greenplum resources for data scientists
Added by Vincent Granville on December 15, 2011 at 3:30pm — No Comments
Clustering algorithm to approximate functions
The strategy is very easy to describe:
1. Divide the domain of your function in k sub intervals.
2. Initialize k monomials;
3. Consider the monomials as centroids of your clustering algorithm.
4. Assign the points of the function to each monomial in compliance to the cluster algo.
5. Use the gradient descent to adjust the parameters of each monomial.
6. Go to 4. until the accuracy is good enough.
Read the entire post at:…
ContinueAdded by Cristian Mesiano on December 15, 2011 at 11:00am — No Comments
Correlation or Causation? | Bloomberg Businessweek
Correlation may not imply causation, but it sure can help us insinuate it.
Source: …
ContinueAdded by Vincent Granville on December 14, 2011 at 1:58pm — 1 Comment
5 Companies That Are Using Big Data & Gamification To Disrupt Market Research | Greenbookblog.org
Posted by Leonard Murphy.
Added by Vincent Granville on December 12, 2011 at 9:00pm — 1 Comment
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