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SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

New Trends In Big Data

Big Data means a huge amount of data and is characterized by 3Vs: Volume, Velocity, and Variety. Big Data has become very clumsy. So, the trend is shifting towards Fast Data, which means processing of massive data in real time to gain instant awareness and detect signals of interest on the spot. Another trend is Actionable Data, which synthesizes the predictive analytics and what-if analysis which enables you to take actions with feedback. Another new trend is Relevant Data which is critical to identify pertinence in the data set, and which leads to understanding of unrelated events and sequence. The last trend is Smart Data which is meaning-based computing and cognitive analytics that make solutions intelligent and self-improving. In a nutshell, Fast Data, Actionable Data, Relevant Data, and Smart Data (FARS) are replacing Big Data. Read more at: http://www.socialmediatoday.com/technology-data/2015-04-04/big-data-really-dead

 

 

 

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Cognitive Analysis: an emerging breed of powerful analytics

Cognitive Analysis: an emerging breed of powerful analytics

For the very first time in this computing era, it is made possible for machines to learn from experience and penetrate through the complexity of the data and identify associations between them, collectively known as cognitive analytics. This innovation works in a similar manner as of human brains. It processes information, draws conclusion and codifies behaviour and experience into learning. Cognitive analytics has the ability to process and understand exploding volumes of data in real time including data that may contain wide variations of format, structure, and quality. Instead of depending on predefined rules and structured queries to mine answers, cognitive analytics relies on systems that draw from a wide variety of potentially relevant information and connections to generate hypotheses. This process differs from traditional analysis in the way that more data is fed into a machine learning system, the system learns, which results in higher-quality insights and more accurate hypotheses. Read more at:http://deloitte.wsj.com/cio/2014/05/13/human-brain-inspires-new-cognitive-analytics/?KEYWORDS=analytics

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