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Facebook's Big Data: Equal Parts Exciting and Terrifying?

February 18, 2014 by Bernard Marr

Big Data Guru column.

This post looks at the gigantic big data repositories Facebook is creating and discusses the exciting as well as terrifying opportunities to exploit that big data. The question is, does big data analytics put too much power in the hands of a commercial company like Facebook?[read more]

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Amazon: Using Big Data Analytics to Read Your Mind

February 6, 2014 by Bernard Marr
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The Big Data Guru column.

This post looks at Amazon's ability to use big data to predict what we will buy in the future. It discusses Amazon's latest patent filing around anticipatory shipping and the implications of increasingly accurate big data analytics.[read more]

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When Big Data Turns Into a Big Nightmare!

January 22, 2014 by Bernard Marr
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The Big Data Guru column.

For most companies today, data - especially big data - is one of their biggest assets. In this article, I look at one big data company that experienced the big data nightmare of having up to 110 million customer records stolen by thieves.[read more]

Big Data from Small Devices?

January 18, 2014 by Bruno Aziza
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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]

How Machine Learning Could Result In Great Applications for Your Business

January 11, 2014 by Mark van Rijmenam

Machine learning.

Machine learning is about creating algorithms and systems that can learn from the data they process and analyse. The more data is processed, the better the algorithm will become. It is actually a science of getting computers to act without explicitly being programmed and is a branch of Artificial Intelligence (AI).[read more]

Perfect Information Doesn't Equal Perfect Predictions

December 16, 2013 by Bill Franks

Imperfect predictions / shutterstock

What if we were able to actually know everything there is to know about our customers? What if we were able to understand them as fully as or better than they understand themselves? Would that lead to predictive models that were perfectly able to predict?[read more]

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Music App Predicting the 2014 Top Artists with Big Data

December 11, 2013 by Todd Nevins

Predicting the 2014 top artists with big data.

15 million song identifications per day on the song finding app, Shazam, has provided the Big Data needed to predict who will hit and who will miss in the music scene for 2014. Users activate the mobile app for a few seconds while a song is being played on the radio, TV or even the shopping mall and the app immediately identifies the song and artist.[read more]

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How Big Data Will Change People Management Forever

November 19, 2013 by Bernard Marr

The Big Data Guru column.

Big data will have an impact in so many business areas. In this post I look at how big data is used in people management (or HR) settings to change the measurement, analysis and management of people forever. I believe big data can make a real impact in the area of people management, but only if companies invest in building the big data and analytics skills and expertise now.[read more]

Obstacles to Personal Genetic Testing in the U.S. and Abroad

November 14, 2013 by Travis Korte

There is no reason people should not be able to pay to have their genes sequenced, particularly now that companies such as 23andMe have helped make personal genomics so inexpensive. Broader adoption of personal genetic testing would not only provide more individuals with information on their health profiles and genealogical histories, it would contribute to a dataset that could eventually help medical researchers investigate treatments to many genetic diseases.[read more]

Nuevora Takes Flexible Approach to Big Data Analytics

November 7, 2013 by Tony Cosentino

Predictive Analytics

Nuevora focuses on big data and analytics from the perspective of the analytic life cycle; that is, it helps companies bring together data and process, visualize and model the data to reach specific business outcomes. Nuevora aims to package implementations of analytics for vertical industries by putting together data sources and analytical techniques.[read more]

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9 Amazing Ways Big Data Is Used Today to Change the World

November 5, 2013 by Bernard Marr

the big data guru

I believe that most aspects of business and society will be impacted by big data analytics, but saying big data is used for everything in not helping with the current confusion of how big data is adding value. This post outlines the 9 areas in which big data is used most extensively today to add real value.[read more]

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Science Needs to Be Less Certain

October 21, 2013 by Paul Barsch
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Good science isn’t without question, discovery and even a bit of “humility”—something that scientists of all stripes (chemists, mathematicians, physicists and, yes, even data scientists) should remember. So let’s encourage debate, discussion, testing and re-testing of theories.[read more]

Data Scientists Should Be the New Factory Workers

October 1, 2013 by Travis Korte

The factory environment is a data scientist’s paradise: both highly multivariate and relatively quantifiable. And the increased use of large-scale data analysis in the manufacturing sector could mean good news—not just for recent graduates in statistics and computer science, but also for the U.S. economy.[read more]

Union Pacific Railroad Turned to the Industrial Internet to Stay on Track

October 1, 2013 by Mark van Rijmenam

Predictive analytics help Union Pacific to predict certain derailments days or even weeks before they are likely to occur. Using thermometers, acoustic and visual sensors on the underside of each of its rail carriages they can detect and analyse imminent problems with tracks and wheels. In order for all the data to be transmitted over the vast rail system, they have deployed a fibre optic communications network throughout its rail system.[read more]

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The Math Says Yes, But Human Behavior Says No

September 10, 2013 by Paul Barsch
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Data scientists are busy writing algorithms to optimize employee productivity, improve trucking routes, and update retail prices on the fly. But those pesky humans and their demands for a reasonable schedule and consistent pricing keep getting in the way. Which then proves when it comes to algorithmic model development, “real world” human behavior is the hard part.[read more]