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Big Data Analytics

As of 2012, about 2.5 quintillion bytes of data are created each day and that number is doubling every 40 months or so. More data cross the internet every second than were stored in the entire internet just 20 years ago. Data is produced from pictures, videos, social media posts, intelligent sensors, purchase transaction records, GPS signals, to name a few. Besides mobile phones, online shopping, social networks, electronic communication, GPS and instrumented machinery all produce torrents of data as by-products of their operations. Data does not stop here. Today, each one of us is a walking data generator. This data is both structured and unstructured. There is a huge amount of signal in this noise, waiting to be released. Analytics bring rigorous techniques to decision making and hence makes big data simpler and immensely powerful.

Analytics : The silver lining...

Be it Predictive analysis, Enterprise decision management, Retail analysis, Market optimization, Sentiment analysis, Web analytics, Portfolio analysis, Sales force sizing and optimization, Price and promotion modeling, Predictive science, Credit analysis, Fraud analysis or the success stories of Google, Amazon, Facebook, Twitter, etc., Big Data Analytics can explain it all.

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The 4 V’s of Big Data


Collect a massive amount of data from various sources & store it using new technologies (such as Hadoop).


Manage and utilize any data in any form.


As data streams-in with a tremendous speed, we maintain it in a proper & timely manner.


Test the quality of the data.

“We don’t have better algorithms. We just have more data.”

Peter Norvig, Google’s Director of Research

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