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Big Data

Why is Big Data so important for enterprises by @OpenSourceForU

 Big DataThe five Vs of Big Data
We can identify Big Data with the help of the following characteristics:
1. Volume: Big Data is characterised largely on the basis of the quantity of generated and stored data.
2. Variety: The type and nature of the Big Data helps people who analyse it to effectively use the resulting insights.
3. Velocity: Big Data is also identified by the rate at which the data is generated and processed to meet various demands.
4. Variability: We can consider a data set to be Big Data if it’s not consistent, hampering various processes that are used to handle and manage it.
5. Veracity: In some sets of data, the quality varies greatly and it becomes a challenging task to analyse such sets, as this leads to a lot of confusion during analysis.
The various challenges associated with such large amounts of data include:
1. Searching, sharing and transferring
2. Curating the data
3. Analysis and capture
4. Storage, updation and querying
5. Information privacy


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Improve your inventory management.

 InventoryGood inventroy tracking menas good finantial performance. Using profesional invetory tracking tools improves time managemet and assets knowlege. ADC is the perferct partner for thos goal. learn more at Symtechven


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 IoTWhen on April 3, 1973, Martin Cooper, a Motorola engineer, dialed up their competitor, Joel Engel of AT&T, for the world’s first cellular telephone call from his brick-shaped device while walking in the street, nobody could have realized that this was going to be a disruptive technology in the coming decade and would continue to be today.
The public launch of Friendster in March 2003 [2] (by Jonathan Abrams, a Canadian programmer) gave birth to the disruptive technology-intensive platform that evolved as “social networking.” Interestingly, even its former CEO, Kent Lindstrom, saw it as nothing more than “the idea was to have the Internet do the work of a dinner party” [3]. The senior editor for internet and technology of Fortune magazine, David Kirkpatrick, also predicted in the same way [4], “There may be a new kind of internet emerging–-one more about connecting people to people, than people to websites,” or as visualized by Mark Pincus, an investor in Friendster and founder of Tribe.net, as a “peopleweb.”

We are living in an age where we are witnessing an explosion of innovation supported by killer technologies triggering disruptions. The complete business landscape of opportunities and challenges is accelerating at a whooping rpm. This is the “digital age.” This accelerating change is supersonic, or even much more than that. It is like floating in a gravitational field of 4G. Businesses have to acclimatize and evolve in sync with this pace. Otherwise, they will perish once they reach a tipping point.


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Low-cost solar cells poised for commercial breakthrough. by Robert F. Dec 2016 @sciencemagazine

 EnergyCheap materials called perovskites are insinuating themselves into silicon solar cells—a first step toward ultimately usurping the reigning cell material. Last week, at a meeting here of the Materials Research Society (MRS), researchers announced that “tandem” cells, in which perovskites are layered on top of silicon and other photovoltaic materials, have achieved record-setting efficiencies at turning sunlight into electricity. Now, researchers are moving fast to surmount the lack of durability and other problems that have hindered the commercialization of perovskites.

“I think perovskites are going to make it to market,” says Aslihan Babayigit, a perovskite researcher at Hasselt University in Diepenbeek, Belgium. The progress has been “amazing,” adds David Cahen, a materials scientist at the Weizmann Institute of Science in Rehovot, Israel. “Even if all the problems are not solved, most look solvable.”


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People unfamiliar with its technical meaning will describe some sort of background noise

 NoiseThe term white noise is fairly common. People unfamiliar with its technical meaning will describe some sort of background noise, like a fan, as white noise. Less common are terms like pink noise, red noise, etc.

The colors of noise are defined various ways, but they’re all based on an analogy between the power spectrum of the noisy signal and the spectrum of visible light. This post gives the motivations and intuitive definitions. I may give rigorous definitions in some future post.

White noise has a flat power spectrum, analogous to white light containing all other colors (frequencies) of light.



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