Big, Big Data
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Big, Big Data
As data scales, it becomes more useful
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Researchers develop battery-free communication tech for Internet of Things sensors

Researchers develop battery-free communication tech for Internet of Things sensors | Big, Big Data | Scoop.it

"Thinking ahead to a world where hundreds of millions of wireless sensors are embedded in consumer electronics and mobile health devices, researchers are developing a new technology that would use existing wireless and TV radio waves to power sensors without batteries.

 

Researchers at the University of Washington have developed a new technology, which they call "ambient backscatter," that will allow devices to communicate with each other by reflecting the existing radio signals around them. The researchers built small, battery-free devices with antennas that can detect, harness and reflect a TV signal, which then is picked up by other devices.

 

The upshot is that such technology could power sensors embedded in wireless devices, enabling more sensors to be deployed. But right now it is not  practical for actually transmitting information: the system can only deliver data at about 1 Kbps over a distance of 2.5 feet outdoors and 1.5 feet indoors. In other words, it won't be sending massive data packets anytime soon. However, the researchers hope to advance their work and have the technology to power sensors placed permanently on any structure."

 

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What a big data business model looks like

What a big data business model looks like | Big, Big Data | Scoop.it

The rise of big data is an exciting — if in some cases scary — development for business. Together with the complementary technology forces of social, mobile, the cloud, and unified communications, big data brings countless new opportunities for learning about customers and their wants and needs. It also brings the potential for disruption, and realignment. Organizations that truly embrace big data can create new opportunities for strategic differentiation in this era of engagement. Those that don't fully engage, or that misunderstand the opportunities, can lose out.

 

There are a number of new business models emerging in the big data world. In my research, I see three main approaches standing out. The first focuses on using data to create differentiated offerings. The second involves brokering this information. The third is about building networks to deliver data where it's needed, when it's needed.

 

* Differentiation creates new experiences.

 

* Brokering augments the value of information.

 

* Delivery networks enable the monetization of data.

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Big Data: the key to solving healthcare's data problems?

Big Data: the key to solving healthcare's data problems? | Big, Big Data | Scoop.it

Lorraine Lawson writes:

 

'Oracle recently released a report noting, among other things, that healthcare isn’t prepared to manage Big Data. That’s hardly shocking, since healthcare seems largely inept at managing any data, much less Big Data, which is generally defined as having one or more of these characteristics:

 

* Variety, meaning structured, semi-structured and unstructured data
* Velocity, meaning you want it moved at high speeds
* Volume, think petabytes and terabytes

 

Maybe health care IT doesn’t have a data problem so much as it has a Big Data problem.

 

What do I mean? Well, most health care records actually fall into the domain of Big Data more than your typical, relational database kind of data. Specifically:

 

* Most health care records are actually unstructured data, e.g., text documents or images. Doctor’s notes on patients, nurse’s care plans, lab results, x-rays and MRI results all fall well outside the domain of structured data. I


* Health care data is often high volume, particularly when you’re talking about a state or national electronic health records system. What’s more, when you deal with images, like x-rays or other scans, you’re increasing the data’s volume in terms of storage requirements.


* Finally, most health care records need to be moved relatively quickly, and as individual records. So, if I’m having a consult tomorrow with a surgeon, then the x-rays need to be at the office by morning.

 

It looks like there’s a clear use case for Big Data technologies in health care.

 

In fact, if I may be so bold, maybe health care’s data problems are not entirely caused by niche vendors, data silos and a lack of investment.

 

Maybe the reason health care IT is such a mess is because the existing tools couldn’t handle Big Data needs in an affordable way.

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'We won’t have the human or technological capacity to analyze Big Data accurately and efficiently by 2020'

“A lot of 'Big Data' today is biased and missing context, as it's based on convenience samples or subsets,” said Dan Ness, principal research analyst at MetaFacts

 

“We're seeing valiant, yet misguided attempts to apply the deep datasets to things that have limited relevance or applicability. They're being stretched to answer the wrong questions. I'm optimistic that by 2020, this will be increasingly clear and there will be true information pioneers who will think outside the Big Data box and base decisions on a broader and balanced view. Instead of relying on the 'lamppost light,' they will develop and use the equivalent of focused flashlights.”

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Salesforce.com goes for social big data with radian6 updates

Salesforce.com goes for social big data with radian6 updates | Big, Big Data | Scoop.it

Salesforce.com has updated its Radian6 social media monitoring software with the introduction of Insights, expanding analysis beyond sentiment to include intent, demographics and online influence.

 

The updates will help companies deal with the deluge of data from social networks such as Facebook, Twitter and LinkedIn as well as blogs, forums and sites like YouTube, salesforce.com said.

Salesforce Radian6 Insights brings on board a number of partners to improve its analytics capabilities: Clarabridge for text sentiment analysis, Lymbix for emotion and tone understanding, PeekAnalytics for social audience measurement, Solariat for intention analysis and OpenAmplify for customer service capabilities.

 

These companies join Klout and OpenCalais, who were already partners.

 

Capabilities such as sentiment analysis and certain demographic information have been available in Radian6 for a while now, but this latest update extends those features a little more, the company told CBR.

 

Radian6 product marketing manager Gordon Evans said sentiment analysis has been upgraded to include foreign languages and demographic information can be pulled from biographies on sites like Twitter and Facebook.

 

The company used the tweet "I'm loving the Apple keynote. Totally want to get the new iPad. When is it coming out?" as an example of what the new Radian6 can do. The tool can pull sentiment ("loving"), company info ("Apple"), intent ("want to get"), product ("new iPad") and customer service ("When's it coming out?") from that one tweet, providing the company with a lot of useful information they can act on.

 

"People are sharing more and more information thanks to sites such as Facebook and Twitter," Gordon Evans said. "There is a huge volume of social data out there and we want to go beyond just listening to get meaning and actually understand what is being said."

Insights also comes with a new dashboard that enables users to scroll through the various options for analysis, depending on which additional services have been signed up for.

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Better medicine, brought to you by big data

Better medicine, brought to you by big data | Big, Big Data | Scoop.it

Slowly but surely, health care is becoming a killer app for big data.

 

Whether it’s Hadoop, machine learning, natural-language processing or some other technique, folks in the worlds of medicine and hospital administration understand that new types of data analysis are the key to helping them take their fields to the next level.

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Text mining: what do publishers have against this hi-tech research tool?

Text mining: what do publishers have against this hi-tech research tool? | Big, Big Data | Scoop.it
Researchers push for end to publishers' default ban on automated computer scanning of tens of thousands of papers
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Mobile now accounts for 10% of Internet usage worldwide, double that of 2010

Mobile now accounts for 10% of Internet usage worldwide, double that of 2010 | Big, Big Data | Scoop.it

Mobile now accounts for 10 percent of all Internet usage worldwide, after the rise in demand and ownership of smartphones and tablets saw the proportional use of the mobile Web more than double over the last 18 months

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HealthStartup III: Big Data - call for startups

HealthStartup III: Big Data - call for startups | Big, Big Data | Scoop.it

HealthStartup Europe has announced the third edition of HealthStartup, to be held this June in Nijmegem, The Netherlands:

 

'The theme of this edition is Big Data; therefore we’re looking for startups that place data at the heart of their business model and business proposition.

 

These can include startups that capture, monitor, aggregate, integrate, analyze or visualize health-related data for any number of purposes, including patient monitoring, medical diagnosis, medical decision support, medical research, public health monitoring, self-tracking/quantified self, fitness tools, systems integration, and so on.'

 

Health startups that wish to be considered can apply here:

 

http://healthstartup.wufoo.com/forms/healthstartup-registration-form/

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Super-convergence: NIH, Amazon and genomes - in the cloud

Super-convergence: NIH, Amazon and genomes - in the cloud | Big, Big Data | Scoop.it

Amazon and the U.S. National Institutes of Health (NIH) announced today that the complete 1000 Genomes Project is being made available on Amazon Web Services as a public data set.

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Big Data: if you’re not paying for the service, you’re the product

Big Data: if you’re not paying for the service, you’re the product | Big, Big Data | Scoop.it

Jerry Michalski write:

 

'I love big data, and not just because of my background in econometrics. A few things to love about it include:

 

* It’s helping solve big problems.

Early detection of epidemics. Automated spell-checking. Crowdsourced astronomy. We seem to have entered the Age of Big Data.

 

* It’s creating useful feedback loops.

In participatory medicine, people opt in to share data so they can analyze it and continually improve their health outcomes. This kind of feedback is spreading from field to field.

 

* It’s eroding the culture of expertise.

Read Daniel Kahneman’s new book and you’ll stick to statistics. Add a pinch of Taleb and you’ll never speak to tie-wearing experts again.

 

* It’s nurturing a culture of collaboration.

From participatory medicine to open science and open government, scientists and citizens alike are resetting the terms of innovation.

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How Twitter is doing its part to democratize big data

How Twitter is doing its part to democratize big data | Big, Big Data | Scoop.it

'Twitter has been on a tear lately when it comes to open sourcing big-data tools. The latest two are Cassie, a client for managing Cassandra clusters, and Scalding, a MapReduce framework for simplifying the creation of Hadoop jobs.'

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The Big Data connection between poverty and COPD

The Big Data connection between poverty and COPD | Big, Big Data | Scoop.it

Credit ratings company Experian has ranked every English local authority by a set of key poverty indicators including greatest likelihood to contain households at risk of chronic obstructive pulmonary disease (COPD).

 

The data indicate that South Tyneside is the place most at risk with regard to the incidence of COPD.

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At the intersection of the quantified self movement and big data

At the intersection of the quantified self movement and big data | Big, Big Data | Scoop.it
As the quantified self movement expands, so too will the likelihood that patients will want to share their information with physicians.
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Digital health data will improve care and spur debate

Digital health data will improve care and spur debate | Big, Big Data | Scoop.it

Francis Koster writes:

 

In 1854, Dr. John Snow started treating victims of cholera in London. More than 500 people died in the first week the disease surfaced. Desperate to figure out what was causing the epidemic, he worked round the clock for days to hand-draw a map containing the location of all the homes of the sick and dying, and he realized that everyone who was sick got their water from the same well. He persuaded local officials to remove the well pump handle, and the epidemic stopped.

 

Today, a high school student using Google Maps could probably draw that same map in a few minutes by combining death notice addresses and well locations readily available on the Internet.

 

Data mining of accumulating electronic health records across platforms will reframe the healthcare debate.

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Should Facebook's facial recognition features be opt-in only?

Should Facebook's facial recognition features be opt-in only? | Big, Big Data | Scoop.it

Facebook's use of facial recognition technology took heat from Sen. Al Franken and other members of the Senate during a Congressional hearing on Wednesday.


U.S. Sen. Al Franken (D-MN) grilled Facebook over its use of facial recognition technology during a Congressional hearing on Wednesday. Franken argued that the social network should make the feature opt-in, rather than opt-out — a complaint Facebook has heard before concerning matters of user privacy.


Facebook currently uses facial recognition technology for its “Tag Suggestions” feature, which is currently disabled for technical reasons. Speaking to Facebook privacy manager Rob Sherman, Franken recommended that Facebook allow users to choose whether or not they want to enable the feature before turning it back on. To back up his argument, he noted that Google+, which also uses facial recognition, offers this feature as opt-in by default.


When Franken noted that users had to go through six pages of privacy settings to access controls for the Tag Suggestions feature, Sherman said that he “didn’t think it ws that hard to get to but wasn’t sure.” Franken wasn’t impressed.

 

“You’re the guy in charge of all this?” Franken joked.


Sherman defended Facebook’s Tag Suggestions, saying that the feature only suggests that users tag people who they are already friends with on the social network. He also said that no third-parties have access to the facial recognition data collected by Facebook.
“If people don’t trust us, they won’t use our service,” Sherman said.

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Your laptop can now analyze big data

Your laptop can now analyze big data | Big, Big Data | Scoop.it

Computer scientists from Carnegie Mellon University have devised a framework for running large-scale computations for tasks such as social network or Web search analysis efficiently on a single personal computer.

 

The software could help developers working on many modern tasks: for example, designing a new recommendation engine using social network connections. In order to make effective recommendations—"your friends liked this movie, so here is another movie that you haven't seen yet, but you will probably like"—the software has to be able to analyze the connections between the members of a social network. This type of task is called graph computation, and it is increasingly common. But working with large-scale data sets (such as online social networks) usually requires the processing horsepower of many computers clustered together, such as those offered by Amazon's cloud-based EC2 service.

 

The new software, called GraphChi, exploits the capacious hard drives that are becoming ever more common in personal computers. A graph would normally be stored in temporary memory (RAM) for analysis. With GraphChi, the hard drive performs this task instead.

 

"PCs don't have enough RAM to hold an entire Web graph, but they do have hard drives, which can hold a lot of information," says Carlos Guestrin, codirector of Carnegie Mellon's Select Lab, where GraphChi was developed. But hard drives are slow compared to RAM for reading and writing data, which tends to slow down computation. So Guestrin's student Aapo Kyrola designed a faster, less random method of accessing the hard drive.

 

According to Guestrin, a Mac Mini running GraphChi can analyze Twitter's social graph from 2010—which contains 40 million users and 1.2 billion connections—in 59 minutes. "The previous published result on this problem took 400 minutes using a cluster of about 1,000 computers," Guestrin says.

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Discovery in the age of Big Data

Discovery in the age of Big Data | Big, Big Data | Scoop.it

The rapid growth of data creation and collection has driven the need for big data solutions at many organizations. As enterprises look to innovate products and services at a faster pace and improve customer service, they cannot afford to overlook the massive amount of data locked away in data repositories on both sides of the firewall.

 

However, getting the ball rolling on analyzing this fluid data set can be a huge challenge. While some of this information is housed in well-structured databases and applications, invariably a large percentage, perhaps up to 80%, is in complex and unstructured formats spanning multiple systems. In this post I’ll focus on the challenge of discovery in a world of unstructured data.

 

Part of the challenge of working with unstructured data in a big data environment is getting a handle on exactly what type of data you have available. Simply moving everything in bulk into Hadoop clusters and data warehouses is not a viable approach.

 

Successful big data implementations take a phased approach and deciding what data to roll into your big data platform is part of this process. This data exploration phase is critical in developing and understanding what data exists, what is missing and how the data ties to the use case scenarios most important to the business.

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Big Data + Healthcare = Big Win | DataStax

Big Data + Healthcare = Big Win | DataStax | Big, Big Data | Scoop.it

With last year’s McKinsey report saying that the value big data brings to healthcare and related companies is $300B, it’s no surprise that healthcare IT leaders are moving rapidly towards the adoption of big data technologies that it is hoped will help them realize significant benefits.

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Text mining: what do publishers have against this hi-tech research tool?

Text mining: what do publishers have against this hi-tech research tool? | Big, Big Data | Scoop.it
Researchers push for end to publishers' default ban on automated computer scanning of tens of thousands of papers
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How Big Data in health can change medicine

How Big Data in health can change medicine | Big, Big Data | Scoop.it

Leslie A. Saxon, MD writes:

 

'I think about the world in a few years and imagine owning and sharing health data just like we can share our life on social networks.

 

What will billions of heart beats show us?

 

We can use Big Health Data to study life patterns, identify disease, solve endemic health problems, and give us more control over our health.

It’s the beginning of an evolution toward knowing oneself and accepting the commonality of health needs and awareness across humanity. We are trying to tell the story of eight billon heart beats because we know it will help that sick kid in the ER at 3 a.m. in Mumbai, in Bangladesh, in Sao Paulo, in the Bronx, in East Los Angeles, in St. Louis. Everyone in the world can participate, and push medicine toward a health information revolution. This is the Internet of You. That helps 8 billion people. That helps all of us. One heartbeat at a time.'

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Healthcare visualisation maps disease prevalence across America

Healthcare visualisation maps disease prevalence across America | Big, Big Data | Scoop.it

John Burn-Murdoch writes:

 

Regional differences in healthcare have been mapped time and again during the recent rise of online data-visualisation, but this effort, from the folks at AdAge, presents a new approach.

 

The infographic shows which disease is most prevalent within the population of each US county, and also highlights the socioeconomic status of each region, as defined by the Patchwork Nation project.

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The future is quantified: on the convergence of trends

The future is quantified: on the convergence of trends | Big, Big Data | Scoop.it

Angela Dunn (@blogbrevity) reflects on how social, mobile, Big Data and the Internet of Things come together will shape the future.

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Public health insights, hidden in plain sight

'Any single Tweet may seem insignificant, but taken together billions of Tweets can unlock insights to our public health.

 

Michael J. Paul and Mark Dredze analyzed two billion Tweets for relevance to health information and then compared the results to data from the Centers for Disease Control. They demonstrated that Twitter can accurately track the spread of influenza, the peak of allergies and predict how diseases spread and change over time. Their research suggests new uses for big data.'

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Is Big Data just big hype?

Is Big Data just big hype? | Big, Big Data | Scoop.it

'How much is there really to all this big data talk? Is it all about putting new labels on existing product offerings, as some would contend? Or is it the diametrically opposed view, a bunch of interesting but immature technologies that aren’t yet ready for enterprise deployment?

 

And what about the demand side? Are companies asking for these solutions? Do they need them at all?'

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