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Archive for the ‘Big Data’ Category

Is Wifi Signal Harmful?

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Gadgets that we use to connect or to stream WiFi signals work under safety standards in order to protect us from harmful effects. These devices have its own emission of microwave radiation, especially when you have your WiFi card on and you are connected to a router. The signal transmitted by a WiFi router is 100,000 times less than a microwave oven. WiFi routers work with low voltages and broadcast the signals in all directions.  Every time you double the distance between you and the router, you will reduce the intensity of the transmitted energy by 3/4. This means that the highest radiation can be found closest to the router, and as you move away, you will encounter lower radiation. (this is the  same principle of the inverse square law).

People  have reported symptoms like headache, fatigue, stress, sleep disturbances, skin symptoms and muscles stress, all associated with the presence of a WiFi router in their home or at the working space. This happens more often amongst people who suffer from electromagnetic hypersensitivity.

World Health Organisation conducted a study on this subject and concluded that there is no current evidence to confirm the harmful effects of WiFi signal (low-level radiation) on the human body. However, there are few gaps in the current documentation and more research is needed in order to be 100% accurate.

Suggestion:  Try keeping your router at least 3 meters away from your body. Try to switch off your laptop’s WiFi card if you’re not using it and, if you can, use a LAN connection. The best case scenario is to place it away from the room you sleep in.

Walmart Takes On Big Data

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Much of the big data tools have been developed at the Walmart Labs, which was created after Walmart took over Kosmix in 2011. The products that were developed at Walmart Labs are ‘Social Genome’, ‘ShoppyCat and Get on the Shelf.

The Social Genome product allows Walmart to reach customers, or friends of customers, who have mentioned something online to inform them about that exact product and include a discount.
 Public data is combined from the web along with social data and proprietary data such as customer purchasing data and contact information. The result is , constantly changing, up-to-date knowledge base with hundreds of millions of entities and relationships. this provides  Walmart with a  better understanding of  the  what their customers are saying online. An example mentioned by Walmart Labs shows a woman tweeting regularly about movies. When she tweets “I love Salt”, Walmart is able to understand that she is talking about the movie Salt and not the condiment.

The Shoppycat product  developed by Walmart is able to recommend suitable products to Facebook users based on the hobbies and interests of their friends. 

Get on the Shelf  a crowd-sourcing solution that gave anyone the chance to promote his or her product in front of a large online audience. The best products would be sold at Walmart with the potential to suddenly reach millions of customers.

Techfest 2013 and Microsoft’s Predictive Whiteboard

 

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Petition To Unlock Cell Phones Update

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The  petition asking President Obama to oppose a new rule restricting cell phone owners from unlocking their devices has passed the 100,000 signatures needed, meaning the White House now must respond.

The petition,  that now has more than 102,000 signatures, protests a regulation from the Library of Congress that prohibits unlocking phones without the carrier’s permission — even when a customer’s contract with the carrier has expired.

CTIA general counsel Michael Altschul wrote in a blog post  It “makes our streets just a little bit safer by making it harder for large-scale phone trafficking operations to operate in the open and purchase large quantities of phones, unlock them, and resell them in foreign markets”.

The petition is partly symbolic: The Library of Congress and the U.S. Copyright Office are part of the legislative branch, not the executive branch, meaning that Obama cannot overturn the decision even if he disagreed with it.

Congress has the power to rewrite the law, the 1998 Digital Millennium Copyright Act, which hands the Library of Congress the effective power to regulate certain gadgets in the name of copyright law. And a nudge from the administration would speed up any DMCA legislative fixes. Under the DMCA, Americans are broadly prohibited from “circumventing” copyright-related technologies, with criminal penalties targeting people who profit from doing it. But the DMCA gives the Library of Congress the authority to grant exemptions, which it did for cell phone unlocking utilities in 2006 and 2010.

The Library of Congress reversed their position last fall, after lobbying from CTIA, which represents carriers including AT&T, Verizon Wireless, T-Mobile, and Sprint Nextel. It ruled (PDF) the exemption was no longer necessary because there are no “adverse effects” relating to locked phones, and unlocked phones are now readily available.

The Library of Congress’ regulatory turn around doesn’t affect jail breaking or rooting mobile phones, which is currently permitted through at least 2015.

 

BIG DATA AND THE OSCARS

 

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A Data Visualization: The Internet Map

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Can Big Data Survive Without Data Scientist?

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A 2011 McKinsey & Co. survey pointed out that many organizations don’t have  the skilled personnel needed to mine big data for insights and the structures and incentives required to use big data to make informed decisions and act on them.

Big data is a mixture of distributed data architectures and tools like Hadoop, NoSQL, Hive and R.  Data scientists serve as the gatekeepers and mediators between these systems and the people who run the business – the domain experts.

Three main roles served by the data scientist: data architecture, machine learning, and analytics. While these roles are important, but not every company actually needs a highly specialized data team of the sort you’d find at Google or Facebook.

Most of the standard challenges that require big data, like recommendation engines and personalization systems, can be abstracted out. On a per domain basis, however, feature creation could be templatized. What if domain experts could directly encode their ideas and representations of their domains into the system, bypassing the data scientists as middleman and translator?

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Big Data and Hospitals

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Big data is emerging in the hospitals and health industries because systems are collecting large amounts of data on patients every single day. The data comes for a variety of settings — clinical, billing, scheduling and so on. previously, a lot of that data was not leveraged to make patient care and hospital operations better. Recently though, there has been a shift to change that. According to Joel Dudley, MD, director of biomedical informatics for The Mount Sinai Medical Center in New York City, healthcare organizations have come to realize that all of their data can be captured and leveraged as a strategic asset.

Dr. Dudley said, “Big data is not just about storing huge amounts of data. It’s the ability to mine and integrate data, extracting new knowledge from it to inform and change the way providers, even patients, think about healthcare.”

Dr Jain of  Anil Jain, MD, CMIO of Explorys, a healthcare analytics company, and former senior executive director of information technology at Cleveland Clinic,  says Big data will change how physicians take care of patients at an individual level, fostering more personalized support right at a patient’s bedside.

“The analysis to deal with big data can produce valid and relevant data that is more current, which gives physicians the means and motivation to make the right decisions at the right time,” says Michael Corcoran, senior vice president and chief marketing officer of Information Builders, a business intelligence and software solutions company.

• The federal push for electronic health records has increased the number of hospitals and providers who use them, subsequently increasing the amount of electronic data generated.
• Newer reimbursement models and accountable care organizations need large amounts of information to be analyzed in order to more accurately understand what occurs with patients.
• New technology in general, including devices, implants and mobile applications on smartphones and tablets, has increased the amount of data available to providers.

According to Dr. Robicsek, MD, vice president of clinical and quality informatics at NorthShore University Health System in Evanston, Il, Big data also provides predictive models for the likelihood of readmission within 30-days which is another area NorthShore is targeting with its big data and informatics work.

 

 

Data Becoming Bigger and Better 2013

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Microsoft Windows Azure HDInsight

There are  companies trying to make Hadoop more useful by turning it into a platform for something other than running MapReduce jobs. The companies – ContinuuityPlatforaDrawn to Scale

 

Differential Privacy and Big Data

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Microsoft research is developing Differential Privacy technology that would serve as a privacy guard and go-between when researchers search databases. It would ensure that no individual could be re-identified, protect privacy by keeping people anonymous in databases, but still help researchers sort big data.

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Big Data

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After having been accustomed to terms like MegaByte, GigaByte, and TerraByte, we must now prepare ourselves for a whole new vocabulary, such as PetaByte, ExaByte, and ZettaByte which will be as common as the aforementioned.

Dr Riza Berkan CEO and Board Member of Hakia provides a list of  Mechanisms generating Big Data

  • Data from scientific measurements and experiments (astronomy, physics, genetics, etc.)
  • Peer to peer communication (text messaging, chat lines, digital phone calls)
  • Broadcasting (News, blogs)
  • Social Networking (Facebook, Twitter)
  • Authorship (digital books, magazines, Web pages, images, videos)
  • Administrative (enterprise or government documents, legal and financial records)
  • Business (e-commerce, stock markets, business intelligence, marketing, advertising)
  • Other

Dr Riza Berkan says Big Data can be a blessing and a curse.

He says that although there should be clear boundaries between data segments that belong to specific objectives, this very concept is misleading and can undermine potential opportunities. For example, scientists working on human genome data may improve their analysis if they could take the entire content (publications) on Medline (or Pubmed) and analyze it in conjunction with the human genome data. However, this requires natural language processing (semantic) technology combined with bioinformatics algorithms, which is an unusual coupling at best.  Two different data segments in different formats, when combined, actually define a new “big data”. Now, add to that a 3rd data segment, such as the FBI’s DNA bank, or geneology.com and you’ll see the complications/opportunities can go on and on. This is where the mystery and the excitement resides with the concept of big data.

Super Big Data Software

Dr Riza Berkan asks are we prepared for generating data at colossal volumes? and we should look at this question in two stages: (1) Platform and (2) Analytics “super” Software

Apache Hadoop’s open source software enables the distributed processing of large data sets across clusters of commodity servers, aka cloud computing. IBM’s Platform Symphony is another example of grid management suitable for a variety of distributed computing and big data analytics applications. Oracle, HP, SAP, and Software AG are very much in the game for this $10 billion industry. While these giants are offering variety of solutions for distributed computing platforms, there is still a huge void at the level of Analytics Super Software . Super Software’s main function would be to discover new knowledge which would otherwise be impossible to acquire via manual means says Dr Berkan.

Discovery requires the following functions:

  • Finding associations across information in any format
  • Visualization of associations
  • Search
  • Categorization, compacting, summarization
  • Characterization of new data (where it fits)
  • Alerting
  • Cleaning (deleting unnecessary clogging information

Moreover, Dr Berkan says that” Super Software would be able to identify genetic patterns of a disease from human genome data, supported by clinical results reported in Medline, and further analyzed to unveil mutation possibilities using FBI’s DNA bank of millions of DNA information. One can extend the scope and meaning of top level objectives which is only limited by our imagination.”

Then too, Dr Berkan says big data can also be a curse  if the cleaning (deleting) technologies are not considered as part of the Super Software operation. In his  previous post, “information pollution”, he emphasized the danger of uncontrollable growth of information which is the invisible devil in information age.

credits: Search Engine Journal/SEG

 

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