Data Exhaust to encourage Big Data

Data Exhaust to encourage Big Data_data_exhaust2b_suman_paul

We are very familiar with the term “Exhaust”. As we know Exhaust means the ‘Byproduct’, released by during the transformation of its parent or primary product. For example, the exhaust gas releases by a car is the byproduct of the fuel used in to run it.

Today we will know about “Data Exhaust”. Wondered with this term?  Don’t worry, let’s clear it up.

The term Data Exhaust came into the picture after creation of excessive data in the digital world. We are being creating data piles at each and every instance of time and as a results a numerous galaxy of data are being created every day.

What is Data Exhaust?

Data exhaust refers to all those data generated by the digital activities, including information about habits and preferences of its generator. Basically, each and every data can be considered as Data Exhaust once they are used.  The exhausted data can be used to target its generator by providing the desired solution for them.

Let’s take an example of a Book: A book having 300 pages filled up by informative contents. The data written in the book cannot be considered as exhausted data for a reader until the reader does not grasp whole information written in the book. But, when a reader grasps the whole information, then only the data of the book will be considered as exhausted data for that particular reader.

Similarly, the data of debit and credit details of a customer is very important for a bank as compare to the keeping information about the data created by him/her as an action of debiting money from an ATM. Once a customer debits money from an ATM, the information (Data) created by him/her is considered as exhausted data, because the customer got what they wanted and now there is nothing to do with that information. This is what we call as Data Exhaust.


Is Exhausted Data important to Us ?

Yes! Data Exhaust is important for us but not entirely. Actually, importance of data exhaust depends upon the characteristics of generated data.

Let’s take a scenario, you are having a casual chat with your friend over smart phone, you both are creating data, the data remains important for both of you until you did not go through it, but once you both went through those data, they become garbage for both of you. In this case these exhausted data are useless for us but in another case where you are debiting money from an ATM, the data is useless until you do not come across any trouble with your transaction. But, when you face an issue with your transaction history, you will raise a claim in the bank in order to solve your issue regarding the particular transaction.

In the second case the bank can only fix your problem by fetching information from the exhausted data dump. Here, you can see the exhausted data is important.

Hence, you cannot decide that the data exhaust is useful or useless until you know about the characteristic of data. But the probability says “Somehow, Exhaust Data are useful”.

Impact of Data Exhaust

From above explanation you have understood, the rapid growth of data is the result of digital activities. According to the statistics of data growth, data scientists are speculating that there will be 8000 Exabyte data created by us at the end of 2021. To handle these enormous volume of data is going to be the next main challenge for the data analytic professionals because Human can able to access only 10% of data from this data ocean. To handle rest 90% of data, a new concept is introducing which is called as Big Data, Machine learning and Digital Martechking.

To know more about Big Data keep reading my blogs and You can also raise your query at “my forum” given in the forum section of this website.


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