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Statistics

The Great Debate: SAS vs. R

April 14, 2014 by Linda Burtch

SAS vs. R.

Despite hearing more about R from clients and candidates than ever before, determining whether R was actually more popular than SAS proved difficult. A quick Google search for “R vs. SAS” returns more than a few pages dedicated to each side, as well as several heated LinkedIn discussions relating to the topic, with no definitive answers.[read more]

Big Data from Small Devices?

January 18, 2014 by Bruno Aziza
1

Wearable tech.

When it comes to big data, the industry has shown no shortage of predictions for 2014. In fact, you might have read about insights on women in data science, ambitions for Machine Learning or a vision for the consumerization of Advanced Analytics.[read more]

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Time is Money: Milliseconds Matter [INFOGRAPHIC]

December 21, 2013 by Michele Nemschoff

Time is money.

Did you know just a one second increase in Amazon's page load time could potientially cost the retail giant $1.6 billion in annual sales? There's no question consumer online shopping expectations are at an all-time high. But did you know the time they spend on your site is at an all-time low?[read more]

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Be Wary of the Science of Hiring

December 10, 2013 by Paul Barsch
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Risky Business column.

While reliance on experience/intuition to hire “the right person” is rife with biases, there’s also danger in over-reliance on HR analytics to find and cultivate the ultimate workforce. While HR analytics seems to have room to run, there’s still the outstanding question of whether “the numbers” matter at all in hiring the right person.[read more]

Statisticians Push Back Against the "End of Theory" Problem

August 28, 2013 by Travis Korte

For years, some commentators have worried that increasing volumes of data coupled with better and better automated prediction methods would lead to an “end of theory.” Dr. Ryan Tibshirani, an Assistant Professor of statistics at Carnegie Mellon University, is trying to fix that.[read more]

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Big Data and Your Body

July 26, 2013 by Josh Polsky

(image: Norbert von der Groeben & Stanford University)

You can now get data output on your own output. This data-collecting toilet has been around for a few years, but with the emphasis on data collection of every kind becoming the norm, it only seems natural to revisit this invention, as well as similar technologies, and the benefits they present.[read more]

Statistics vs. Data Science vs. BI

May 17, 2013 by David Smith
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Statistician's profile

As someone who trained as a statistician, I've always struggled with that title. I love the rigor and insight that Statistics brings to data analysis, but let's face it: Statistics — the name — has always had a bit of a branding problem. That's why I'm a fan of the term "data scientist."[read more]

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What's the Difference between Desktop BI and Solution BI?

May 17, 2013 by Jim King

A tale of two BIs

All modern Information Technologies which are capable of improving the enterprise competitiveness fall in the scope of BI, such as ERP, CRM, Reporting tools, Data Computing, Statistical Analysis, Data Mining, OLAP, and ETL, etc. They can be divided into two categories: Desktop BI and Solution BI.[read more]

When Data Flows Faster Than It Can Be Processed

April 29, 2013 by Vincent Granville
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data flow

With big data come a few challenges. What can we do when data flows faster than it can be processed? There is a solution that benefits everyone (users, companies such as Google, Amazon, Netflix, Facebook or Twitter, and clients): better use of data science.[read more]

Don't Gloat Over Excel Model Failures

April 23, 2013 by Paul Barsch
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Two noted economists, Kenneth Rogoff and Carmen Reinhardt, recently made an Excel spreadsheet error that led to some grave miscalculations. But just because mathematical calculations are wrong, it doesn’t mean a particular idea isn’t directionally sound.[read more]

Spreadsheets: Still the King of Business Intelligence Tools

April 9, 2013 by Jim King
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Spreadsheets and BI / shutterstock

The year of 2012 witnessed a sharp and substantial increase of BI. Unexpectedly, the spreadsheet turns out to be the one developed and welcomed most, instead of other more sophisticated BI tools like SAP BusinessObjects or Qlikview. Why is the spreadsheet still ruling the BI world?[read more]

Analytics and Hedgehogs: Lessons from the Tampa Bay Rays

April 8, 2013 by Paul Barsch

Analytics lessons via Tampa Bay / shutterstock

The Tampa Bay Rays spend significantly less on payroll than some of their wealthier rivals do, but sometimes get better results. Their success boils down to two things – understanding how to be a hedgehog, and continual application of statistics and analytics into daily processes.[read more]

Stat Models, Astronomical Mysteries…and Business Data

April 6, 2013 by Vincent Granville

Statistical models for the stars

Can the concept of signal amplification be used to gain better, more accurate insights from Big Data? Business data has its own clouds, both metaphorically and physically, making statistical inference, pattern detection, and insights discoveries more difficult.[read more]

Analytical Cultures: Nurture Yours Through Training

March 25, 2013 by Stefan G. Brenner

Nuture analytical cultures

If we want to harvest good things from our organizations, we have to nurture the culture. We can do a number of things to influence the harvest. One of the biggest mistakes organizations make that prevent an analytic culture from taking hold is not investing in ongoing education/training.[read more]

NCAA Data Visualizer for March Madness Face-Offs

March 24, 2013 by David Smith

data visualizer for NCAA

If you're laying down a friendly bet on the March Madness games or just tweaking your fantasy roster, this NCAA Data Visualizer by Rodrigo Zamith will be a boon. Just choose two teams to compare head-to-head, and choose an attribute to compare them on.[read more]