What is Big Data and How Big is this Big Data?



Today Big Data has become the Buzz word of the market. To define what Big Data is, first we have to understand how Big this Big Data actually is.

In naive language if we have to say, its the data that has gone BIG or it will be better to say HUGE.

It’s not that we have started generating data in a day or two. It was there from long, but what has changed is its exponential growth with the growth of technologies.

So from where these data are coming and in what form? To take source examples of a few.


              Videos                                          Emails
                              Transactional Data                   Mobile 
                   Audio                                       Texts
                                 Social Media                                CRM,SCM,ERP 
           IT Ops                                       Seraches

                                                       Images                             And lots more..
         

Lets take a look at the Internet we are using in our day to day life.

Per MINUTE we are Creating
  • 98000+ tweets
  • 695,000 status updates
  • 11,000,000 chat messages
  • 700,000+ Google searches
  • 168 ,000,000+ emails sent
  • 217 new mobile web 
  • A total of 1820 TB data gets created

1 Exabyte(10^18) of data is created on the internet per day. 500 Terabyte(10^12) of new data per day is ingested in Facebook.
Today data scientist uses Yottabyte(10^24)  as the number to describe all the internet data in the world. And we are leading to a world where only our digit universe will be containing Brontobyte(10^27) of data.

So what is the problem with these Huge Numbers. Well the Problem is with the Volume, Velocity, Variety and Complexity.

And in these scenario Big Data provides us with the Tools, Technologies, Tricks and Intelligence to tackle with:
Hence a good definition for Big Data will be

Big Data comes for your rescue when, Dataset whose Volume, Velocity, Variety and Complexity are beyond the ability of commonly used tools to capture, process, store, manage and analyze them.

stats source:  Hewlett-Packard Development PPT




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