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Archive for the ‘Data Scientist’ Category

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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Digital Public Library To Launch April 2012

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Petition To Unlock Mobile Phones

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There’s a Petition to reverse a decision by the Library of Congress making the unlocking of mobile phones illegal that needs 15,000 more signatures by Saturday.

Over 85,000 people have signed a Whitehouse.gov petition asking President Barack Obama to reverse a decision by the Library of Congress making the unlocking of mobile phones illegal under the Digital Millennium Copyright Act (DMCA).

As of Wednesday morning, the petition, started by phone unlocking entrepreneur Sina Khanifar, still needed nearly 15,000 signatures by Saturday to trigger a response by the Obama administration.

Unlocking a phone is typically used to switch carriers. Jailbreaking a phone for the purposes of adding software unauthorized by the carrier or phone maker remains legal under the DMCA. It’s unlikely mobile carriers will seek prosecution for individual phone users, but operators of businesses that help consumers unlock their phones could face penalties of up to a $500,000 fine under the DMCA.

Khanifar said this week he’s optimistic 100,000 people will sign it by Saturday. The petition has recently won endorsements from Representative Peter DeFazio, an Oregon Democrat,

DH Awards Voting 2012

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European Association For Digital Humanities

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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.

 

 

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

 

Big Data and the Legal Profession

 

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IBM’s Understanding Big Data e-book

 

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BYOD

Gartner says, Bring Your Own Device is an alternative strategy that allows employees, business partners and other users to use a personally selected and purchased client device to execute enterprise applications and access data. For most organizations, the program is limited to smartphones and tablets, but the strategy may also be used for PCs. It may or may not include subsidies for equipment or service fees.

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Big Data and Other Technologies

 

Currently Big Data is  synonymous with technologies like Hadoop, and the “NoSQL” class of databases like Mongo (document stores) and Cassandra (key-values).  Today it’s possible to stream real-time analytics with ease. Spinning clusters up and down is a (relative) cinch, accomplished in 20 minutes or less.

Now there are new untapped open source technologies out there.

STORM AND KAFKA

Storm and Kafka are used at a number of high-profile companies including Groupon, Alibaba, and The Weather Channel.

Storm and Kafka is said to  handle data velocities of tens of thousands of messages every second.

Drill and Dremel said to  put power in the hands of business analysts, and not just data engineers.

R

R is an open source statistical programming language. It is incredibly powerful. Over two million (and counting) analysts use R. R works very well with Hadoop

GREMLIN AND GIRAPH

Gremlin and Giraph help empower graph analysis, and are often used coupled with graph databases like Neo4j or InfiniteGraph, or in the case of Giraph, working with Hadoop.

SAP HANA

SAP Hana is an in-memory analytics platform that includes an in-memory database and a suite of tools and software for creating analytical processes and moving data in and out, in the right formats.

 

Big Data and High Performance Comouting

 

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New York City Show Promising Sign to Becoming The Next Silicon Valley

Tech Giants Google and Facebook have shown their presences in New York in recent years. Some big-name newcomers are headquartered here. Plans for an elite technology graduate school, attracted with city money, are getting enough attention that a federal patent officer is being stationed on campus in a first-of-its-kind arrangement.

Entrepreneurs say New York also faces particular challenges, including problematic broadband access in a few areas and a limited tech talent base, though the city is trying to address the concerns. New York solid ground so to speak in financial technology and online publishing, but the growth of social media and digital marketing opens new prospects for a city known for communications, design and advertising. Some prominent start ups  include Foursquare, Tumblr, Kickstarter and Gilt Groupe. They were established in New York in the past five years.

The city’s biggest  move was : offering 12 acres of land and up to $100 million in improvements for a tech-focused graduate school. Cornell University and Technion-Israel Institute of Technology won a competition to run the school, set to start with a handful of students in January. It will be the first institution in the country to boast about an on-campus patent officer, acting U.S. Commerce Secretary Rebecca Blank announced this month. Columbia University and New York University were also offered $15 million apiece in incentives to create new technology programs.

 

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