1
Aug

Why Hadoop Is Important In Handling Big Data?

This is a guest post written by Jagadish Thaker in 2013. Hadoop is changing the perception of handling Big Data especially the unstructured data. Let’s know how Apache Hadoop software library, which is a framework, plays a vital role in handling Big Data.  Apache Hadoop enables surplus data to be streamlined for any distributed processing system across clusters of computers using simple programming models. It truly is made to scale up from single servers to a...
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21
Jun

5 Reasons to Get a Degree in Big Data Analytics

Guest post by Tonya Chestnut, Associate Director of Admissions at Florida Polytechnic University. The study of science, technology, engineering and mathematics (STEM) is taking the field of big data analytics to new heights. Students pursuing a degree in big data analytics study the process of analyzing large datasets to discover patterns, connections and other useful, pertinent information revealed by data. Companies are increasingly turning to data analytics to harness customer insights to produce better business decisions to...
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8
Dec

Why I Think the DIKW Pyramid Should not Be a Pyramid

The world of big data is evolving rapidly and the general public is starting to adopt it as their own. The question that often arises is; we want to do ‘something’ with big data, but what? For large companies this question is easily solved by hiring data scientists. Sure, there are many useful tools out there that show graphics from which you can extract conclusions. However, small and medium-sized companies often don’t know where to...
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13
Nov

How Your Data Can Turn Black Friday into a White Christmas

How your data can turn Black Friday into a White Christmas Returns are a huge area of concern for many retailers; indeed, the sale has not been completed until the customer actually decides to keep the product. But with Black Friday around the corner, and all of the flash buying that entails, can you predict what products are going to cause you the most problems, or even each which customers could give you a headache?
24
Sep

Publishing in a Time When Data Is All Around You

For one, the common knowledge is that you’d have to be really big in the publishing universe to use such tools. Secondly, most people, Marcello Vena thinks, don’t understand the difference between analyzing big data and “normal” data. He distinguishes three key features that set these two kinds of analysis apart. Big data uses a very large volume of unstructured data that standard database management systems simply cannot cope with. Big data needs “adequate data-centric...
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23
Sep

Playing the Big Data Game – 5 Things You Need to Know About the Games of the Future

We’re in the golden age of gaming. In the US, more than half the households now own a console. Tablets and smartphones are packed with games. The video game market has already topped the movies and music markets. From a juvenile distraction to a mostly grown-up entertainment, this momentum is not about to dissipate. If anything, with the help of big data, it’s increasing faster than ever. You probably don’t know what this is. It’s...
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29
Jul

Beating Addiction with Big Data

In a previous post, I wrote about the various applications of big data insights in the gambling industry, from tailored marketing initiatives to odds calculation. However, the very same data used to great commercial effect by gambling companies could have another utility: protecting customers from addiction. Gambling brands are under increasing pressure to either relinquish their data insights to independent regulators or take internal measures to protect their customers. But what exactly is being proposed?...
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12
May

Becoming a Data Scientist: What a Data Scientist ISN’T

If you’re reading this you probably already have an inkling of what a data scientist is. Have you ever considered what a data scientist isn’t? According to Vincent Granville, author of Developing Analytic Talent: Becoming a Data Scientist, data scientists are: Not statisticians Not data analysts Not computer scientists Not software engineers Not business analysts Data scientists do have some knowledge in each of these areas but also some outside of these areas. NEITHER STATISTICIANS...
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