A New Society, a new education!

Ever since Darwin, scientists have systematically analyzed facial expressions, finding that many of them are universal. Humans are remarkably consistent in the way their noses wrinkle, say, or their eyebrows move as they experience certain emotions. People can be trained to note tiny changes in facial muscles, learning to distinguish common expressions by studying photographs and video. Now computers can be programmed to make those distinctions, too.

Companies in this field include Affectiva, based in Waltham, Mass., and Emotient, based in San Diego. Affectiva used webcams over two and a half years to accumulate and classify about 1.5 billion emotional reactions from people who gave permission to be recorded as they watched streaming video, said Rana el-Kaliouby, the company’s co-founder and chief science officer. These recordings served as a database to create the company’s face-reading software, which it will offer to mobile software developers starting in mid-January.

This is an emerging field and complements some of the post GFC analytics . e.g. people who take less than 3 weeks leave in 1 stint are more likely to have breached policies...add to that facial and voice recognition. A UK university was looking at IR camera's in immigration based upon the hypothesis that 'untruth' caused greater brain activity that could be picked up on an IR camera as a trigger for deeper enquiry. Sentiment++

Information from faces ans how to turn information into knowledge

Very interesting infographic.  Why do they fail?  For all of the reasons above and then some...    Over 80% of the data being collected today is unstructured and not readily stored in relational database technology burdened by complex extract, transform and load.  There's also pre-existing data, sometimes referred to as "dark data" that includes documents which need to be included and made discoverable for a host of reasons - compliance and regulatory issues are one.   Log activity and e-mail traffic used to detect cyber threats and mitigate risk through analysis of file transfers is yet another set of data that requires immediate attention.

Social and mobile are clearly channels that need to be addressed as organizations continue to mine data from the open web in support of CRM, product alerts, real time advertising options and more.  

To accomplish all of this, organizations need a platform with enterprise hardened technology that can ingest all of these forms of data in real time, without having to write complex schemas.   Getting back to the point - What do most projects fail?   If companies attempt to do this with technology that is not reliable, not durable and does not leverage the skills of their existing development organization, the project will fail.  

We have seen this time and time again.   MarkLogic to the rescue.   With over 350 customers and 500 big data applications, our Enterprise NoSQL approach mitigates the risk.  Why?  Our technology stack includes connectors to Hadoop, integration with leading analytics tools using SQL, Java and Rest APIs, JSON support, real time data ingestion, the ability to handle any form of data, alerting, in database analytics functions, high availability, replication, security and a lot more.  

When you match this technology with a world-class services organization with proven implementation skills, we can guarantee your next Big Data project will work.  We have done it hundreds of times with the largest companies in the world and very, very big data.

www.marklogic.com

This is a great infographic - it shows that whilst everyone is doing it (it being "Big Data" - whatever that is...), talent is rare, technology is hard to find and the projects never end.  A far cry from the speed with which companies such as the BBC deployed MarkLogic to serve all data for the sport websites through the Olympics.  Now that was big data, delivered by a talented team in a short space of time.