From time to time, you still come across someone with the opinion that Big Data is nothing more than a scam or a fad, which will be forgotten about soon enough. You might not expect to hear this from me, but they’re actually right.
Why do we love big data? Because of Recommendation Engines. They help us to filter out the noise in this big data world. But how are they doing it? What are the challenges? Get an easy overview onto the technology of today: recommendation engines
Fast data: The next step after big data InfoWorld The way that big data gets big is through a constant stream of incoming data. In high-volume environments, that data arrives at incredible rates, yet still needs to be analyzed and stored.
insideBIGDATA Big Data Challenge: Data Paring insideBIGDATA I think a lot about Big Data and the challenges it proposes. I guess I started thinking about Big Data a long time before I ever heard the term.
Much of what we believe about Big Data is wrong, which will be demonstrated in 2014.For many enterprises, Big Data remains a nebulous goal, rather than a current reality. Yet it's a goal that more and more enterprises are pushing to the top of their priority list. As Gartner surveys have shown, everyone is keen to board the Big Data bandwagon, yet a comparative few really understand why. And as Gartner analyst Svetlana Sicular points out, the myths that hold back Big Data adoption vary depending on where along the adoption curve an enterprise happens to be.In 2014, many of the sillier Big Data myths will crumble to be replaced by increased experience with data-driven applications...
Via Jeff Domansky
“Facebook’s announcement draws a sharp contrast to Amazon Web Services, which has failed to explain how it will power its newly announced data centers in Ohio and India, despite the company’s commitment to use 100% renewable energy,” Greenpeace senior climate and energy campaigner David Pomerantz said.
Amazon's Ohio data center, for example, relies on American Electric Power, which generated 83 percent of its electricity from coal.
The European Commission is working hard on developing a competitive European Big Data market. Last week, as a result of this, the European Digital Forum convened the High-Level Roundtable on Europe’s Digital Future.
Big data is messy data. It’s not enough just to collect it and count it, because there is never just one way to count it. Aside from sheer quantity, there are three defining characteristics of big data. One key big data difference is megasourcing: taking data from huge numbers of distributed sources.Another is automation. The ability to analyze data as fast as it can be collected means that the results can be put in play automatically, without anyone having to examine the data manually. Finally, there is the issue of feedback. Big data, then, is good for when you want incremental optimization rather than a killer paradigm shift.
Cloudera's Strategy for Conquering Big Data The Enterprise Forbes Late last year I had a long talk with Amr Awadallah, CTO of Cloudera about the strategy his company was pursuing to dominate the arrival of big data in the enterprise.
Best Big Data Graphics - As I read through many reports, white papers, press releases, magazine articles and company presentations it occurred to me that visually communicating the value of Big Data is challenging because of the need to convey different concepts simultaneously.
What is Big Data? Why is Big Data so important? Who are your Big Data key players? How do you lead with Big Data? Which Big Data solutions do you need? When do you start with Big Data? Explore the Universe of Big Data.
Via Luca Naso
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