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Featured Blog Posts – November 2015 Archive (101)

How Publishers Utilize Big Data for Audience Segmentation

By Chuck Currin and Arvid Tchivzhel, Mather Economics

Audience segmentation of their readers is a relatively new undertaking for publishers. The publishing business model, historically, has relied heavily on advertising revenue, and the principal audience information that a publisher possessed was focused on characteristics valuable to their advertisers. As subscription revenue has become half or more of total revenue, the return on audience analytics and segmentation has…

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Added by Arvid Tchivzhel on November 17, 2015 at 5:28am — No Comments

Eight IOT Analytics Products

Vitria IoT…

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Added by Gilboz on November 17, 2015 at 12:20am — 1 Comment

What Is Unsupervised Learning?

 Unsupervised learning algorithms are machine learning algorithms that work without a desired output label. A supervised machine learning algorithm typically learns a function that maps an input x into an output y, while an unsupervised learning algorithm simply analyzes the x’s without requiring the y’s. Essentially, the algorithm attempts to estimate the underlying structure of the population of x’s (in other…

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Added by Aureus Analytics on November 16, 2015 at 10:00pm — No Comments

30 Great Resources and Articles

Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically categorizing them using indexation and automated tagging…

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Added by Vincent Granville on November 16, 2015 at 1:12pm — No Comments

What Is Spark - An Easy Explanation For Absolutely Anyone

Basically Spark is a framework - in the same way that Hadoop is - which provides a number of inter-connected platforms, systems and standards for Big Data…

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Added by Bernard Marr on November 16, 2015 at 12:30pm — No Comments

Sabermetrics: Baseball Analytics and the Science of Winning [Infographic]

Guest blog by our friends at [email protected] Staff…

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Added by William Vorhies on November 16, 2015 at 9:40am — No Comments

MDM Makes M&A Pay Off

Guest blog by  Neil Cowburn, CEO, iMiDiA

 

Mergers and acquisition often bring drama—they…

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Added by William Vorhies on November 16, 2015 at 9:17am — No Comments

Cloud Data Replication and Routes to Business Opportunity

Cloud data replication is good for backups, but what else might you do with it? For forward-looking users, data replication in the cloud is also a lever for better information, increased autonomy, enhanced productivity, and bigger business opportunities down the line. By conserving an untouched valid reference copy of data, users are free to process or change the other replicated instances, according to their individual…

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Added by Sergei Kharchenko on November 16, 2015 at 8:00am — No Comments

8 Analytics & Visualization Firms Who Implement Tableau

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Added by zimlon on November 16, 2015 at 1:04am — No Comments

Internet of Nano Things (IoNT) Market Analysis, Growth, Trends and Forecast by 2020

Nanoscale devices and systems characterized with their size of 100 nanometer and below are predominantly used to study phenomena such as near field behavior in electromagnetics and optics, single-electron effects and quantum confinement in electronics and other effects in biological, fluidic and mechanical systems. Internet of nano things (IoNT) is…
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Added by Madhuri Pawar on November 15, 2015 at 10:30pm — No Comments

Mass Data Simulations

I have been using the term "mass data assignment" in my blogs. I thought I should offer the community some simulated examples. These are simple simulations: all the data is in one place in an agreeable format. The file contents are meant to be easy to peruse. When I was younger, there was a television series called "Stargate SG-1." I have a number of seasons on DVD. In this series, a special branch of the U.S. Air Force visits offworld sites using stable wormholes: teams enter the wormholes…

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Added by Don Philip Faithful on November 14, 2015 at 6:41am — No Comments

What is Python – An Easy Explanation For Absolutely Anyone

Here is another post in which I try to disentangle some of the concepts that underpin today's big data world.  In this post I look at Python, which is an open source…

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Added by Bernard Marr on November 13, 2015 at 11:00am — No Comments

What is Hadoop - An Easy Explanation For Absolutely Anyone

When you learn about Big Data you will sooner or later come across this odd sounding word: Hadoop - but what exactly is it?…

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Added by Bernard Marr on November 13, 2015 at 11:00am — No Comments

What is R? R Explained in less than Two Minutes, to Absolutely Anyone

If you're looking at ways you can harness the power of Big Data analytics in your business, but are not necessarily a techie person yourself, it can be a confusing field…

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Added by Bernard Marr on November 13, 2015 at 11:00am — 9 Comments

Creative Data Engineering Can Drive Data Science Insights: A Datapalooza Dispatch

Guest blog post by James Kobielus.

Data science lives in the details of your projects. But those details are dry as dust if your projects don’t intersect with something about which you care passionately.

Passions are as varied as the data scientists themselves, and immersion in project details is a sure sign of a true data scientist. The first day of Datapalooza in San Francisco brought many working data scientists together to share details of projects that excite…

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Added by Vincent Granville on November 13, 2015 at 10:53am — No Comments

Data Products in 2016

At breakfast last week, my wife and I noticed water dripping out from under our coffee maker.

Saeco Barista, circa 2004 source:…

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Added by Cameron Turner on November 13, 2015 at 8:31am — No Comments

Forex Algorithmic Trading: A Practical Tale for Engineers

A few years ago, driven by my curiosity, I took my first steps into the world of Forex trading algorithms by…

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Added by Irina Papuc on November 13, 2015 at 6:26am — No Comments

Data Science is greater than the sum of its parts

Good post by Kirk Borne. If  you have

  • domain expertise (a),
  • business acumen (b),
  • analytic skills (c),
  • hacking skills (d),
  • coding skills (e),
  • and selling skills - to sell your data science product to your boss (f),

then your potential or value (v) is equal to

v = a * b * c* d * e * f > a + b + c + d…

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Added by Vincent Granville on November 12, 2015 at 9:30pm — No Comments

DJ Patil and The Evolution of the Chief Data Scientist

DJ Patil is arguably the most well-known data scientist in the world. He’s the Chief Data Scientist for the White House, he built the first data science team at LinkedIn, and along with Jeff Hammerbacher, is credited by Forbes as coining the term data scientist.

So, How does Patil's journey compare to those of the…

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Added by Daniel Levine on November 12, 2015 at 10:30am — No Comments

Why 5 Companies Chose Amazon Redshift

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Added by Ogmer on November 12, 2015 at 2:19am — No Comments

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