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What is Big Data? Explain Big Data, Define Big Data, What is Big Data with Examples.
Big Data basically refers to, huge volume of data that cannot be, stored and processed using the traditional approach within the given time frame.
The next big question that comes to our mind is?
How huge this data needs to be? In order to be classified as Big Data?
There is a lot of misconception, while referring the term Big Data.
We usually use the term big data, to refer to the data, that is, either in gigabytes or terabytes or petabytes or exabytes or anything that is larger than this in size.
This does not defines the term Big Data completely.
Even a small amount of data can be referred to as Big Data depending on the context it is used.
Let me take an example and try to explain it to you.
For instance if we try to attach a document that is of 100 megabytes in size to an email we would not be able to do so.
As the email system would not support an attachment of this size.
Therefore this 100 megabytes of attachment with respect to email can be referred to as Big Data.
Let me take another example and try to explain the term Big Data.
Let us say we have around 10 terabytes of image files, upon which certain processing needs to be done.
For instance we may want to resize and enhance these images within a given time frame.
Suppose if we make use of the traditional system to perform this task.
We would not be able to accomplish this task within the given time frame.
As the computing resources of the traditional system would not be sufficient to accomplish this task on time.
Therefore this 10 terabytes of image files can be referred to as Big Data.
Now let us try to understand Big Data using some real world examples.
I believe you all might be aware of some the popular social networking sites, such as Facebook, Twitter, LinkedIn, Google Plus and YouTube.
Each of this site, receives huge volume of data on a daily basis.
It has been reported on some of the popular tech blogs that.
Facebook alone receives around 100 terabytes of data each day.
Whereas Twitter processes around 400 million tweets each day.
As far as LinkedIn and Google Plus are concerned each of the site receives tens of terabytes of data on a daily basis.
And finally coming to YouTube, it has been reported that, each minute around 48 hours of fresh videos are uploaded to YouTube.
You can just imagine, how much volume of data is being stored and processed on these sites.
But as the number of users keep growing on these sites, storing and processing this data becomes a challenging task.
Since this data holds a lot of valuable information, this data needs to be processed in a short span of time.
By using this valuable information, companies can boost their sales and generate more revenue.
By making using of the traditional computing system, we would not be able to accomplish this task within the given time frame, as the computing resources of the traditional system would not be sufficient for processing and storing, such a huge volume of data.
This is where Hadoop comes into picture, we would be discussing Hadoop in more detail in the later sessions.
Therefore we can term this huge volume of data as Big Data.
Let me take another real world example related to the airline industry and try to explain the term Big Data.
For instance the aircrafts, while they are flying keep transmitting data to the air traffic control located at the airports.
The air traffic control uses this data to track and monitor the status and progress of the flight on a real time basis.
Since multiple aircrafts would be transmitting this data simultaneously to the air traffic control.
A huge volume of data gets accumulated at the air traffic control within a short span of time.
Therefore it becomes a challenging task to manage and process this huge volume of data using the traditional approach.
Hence we can term this huge volume of data as Big Data.
I hope you all might have understood, “What is Big Data”.
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“Define Big Data”
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