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Real time analytics of big data

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Real time analytics of big data

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This slide is about real time analytics of Big Data. It explains about Big Data and Analytics. How to deal with them.

see more at - http://bigdataconcept.blogspot.in/2016/03/real-time-analytics-of-big-data.html

This slide is about real time analytics of Big Data. It explains about Big Data and Analytics. How to deal with them.

see more at - http://bigdataconcept.blogspot.in/2016/03/real-time-analytics-of-big-data.html

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Real time analytics of big data

  1. 1. Real Time Analytics of Big data By Deependra Jyoti
  2. 2. Big Data? • Big Data is a collection of large amount of Data that is available with all the organisation. The amount of these data are so huge that managing them has become a challenge. The worst thing is these data are increasing exponentially.
  3. 3. Big Data Example • i) 200 of London's Traffic Cams collect 8 TB of data per day. • ii)1 day of Instant Messaging in 2002 consume 750 GB of Data. • iii)Annual Email Traffic excluding spams consume 300PB+ of Data. • iv)In 2004 Walmart Transacton DB contains 200 TB of Data. • v) Total Digital Data created in 2012 is assumed to be 270000 PB.
  4. 4. Big Data Example
  5. 5. Real Time Analytics • In order to get something meaningful from the huge quantity of data Real Time Analytics is used. • It deals with both structured and unstructured data coming from external source like sensor in order to get a meaningful conclusion.
  6. 6. Example i) Crime detection and prevention ii) Stock Market - In stock market trading happens so fast that a fraction of second change everything. Here if we analyse the pattern in real time then we can generate meaningful conclusion.
  7. 7. iii)Telecommunication - Now a days world is so densely connection that it becomes a headache for the companies to manage the CDR. One can imagine the vast quantity of data present in a CDR. All of the data is not relevant. So in order to store them efficiently Infosphere Stream can be used. It will parse all the details and remove the irrelevant one.
  8. 8. iv)Health monitoring - The system can also be used for proper monitoring of health. Data from devices can be monitored and studies in order to find out if the patient is suffering from some diseases. v) Transportation - Real time data can be available about movement of buses or anything and customer can benefit from it.
  9. 9. Thank You
  10. 10. Thank You

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