Data Analytics
Machine learning and artificial intelligence have become ubiquitous in our everyday lives. Wherever we go, whatever we do, we are constantly interacting with AI in one way or another. From facial recognition and robotics to health and medical diagnosis, systems are changing our lives for a better future. Chatbots are replacing humans for customer service inquiries. Robots are even performing surgery where human surgeons are supervising.
All of these significant advances have changed the way we collect data as the volume has increased tremendously and bigger and better machines are needed to derive big data evolution. Big data comes from myriads of sources including social media, sensors, IoT video surveillance and smart devices. It has become a struggle to keep up with the changing market requirements. Rafson Technologies has been creative and applies big data to growing business needs and increasingly complex problems.
Moreover, how we interact with the real world is intensely data driven. The human brain receives the equivalent of 100 million bytes of sensory information for each second of sensory experience. The eyes alone generate the equivalent of about 90 million bytes of information per second. On a daily basis this is roughly equivalent to 5.76 trillion bytes of data per day. This data is analyzed by the brain’s 100 billion neurons and produces a model of the physical reality that surrounds us-a significant part of what we call consciousness.
The physical reality model enables us to “see” objects and is incredibly useful in making decisions. Each of us makes an enormous number of life and death decisions with this model. Do I have enough time to safely cross the street now or should I wait until the oncoming car goes by? Should I make a left turn now or should I wait until the oncoming bus passes? Data scientists and statisticians do the same sort of thing. They build ML models with data and make decisions using those models. At Rafson Technologies our data analytics professionals develop methods of designing experiments and gathering data that are cost effective and resilient.
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