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" HOUR OF DATA SCIENCE "

Jul 06, 2019 Data Science, 940 Views
An introductory blog about Data Science

THE HOUR OF DATA SCIENCE

Data Science , well I guess if you are an active Internet user I guess you already have come across this word be at any educational purpose or any advertisement at YouTube.

So allow me to make you understand Data Science in really short way and simple, to be very simple Data means something very informative to someone and non informative to someone right? Science is the scientific way to deal with respective field , here we come that how science can help you to understand data efficiently and effectively, so the term Data Science.

 

 
But the question is that why do we need Data Science ? I mean why in after 2015 there is so super need of Data Science. Well the answer is Data is found i mixed form i.e, in form of visual, text or audio , and there are lots of data , so first we need to classify to what we need filter it out , extract what we actually need and then perform what we want to perform, and this task cannot be done without help of Data Science and so "The hour of Data Science".
Well Data Science has some attributes or processes which I guess will be better if we deeply understand them, some of them we will try to understand and will clarify your doubts about what exactly is Data Science.


 

So some of the terms are

  • Data Classification
  • Data Cleansing
  • Data Filtration
  • Data Extraction

Data Classification : Data Classification may be defined as way to actually classify what data is needed out of so many big data, i.e which data is needed to operate in the operation to make sure there isn't any backstore with it.

 

 

 

Data Cleansing : The Act of Cleaning the data out of so many mixed data after classification , to fill missing data , or to correct any wrong data , i.e to reduce or to remove any noise.

 

 

 

Data Filtration :To filter out the operators that are required for the specific purpose to increase out the performance and to remove any sort of mis- calculation bug

 

 

 

Data Extraction : To extract the right requirements such that there isn't any false output by the operation and thus promising optimised output.

 

The world of Data Science is huge and requires huge processing to deliver the optimised result. Documentation can really help the required data to be fetched out and thus helping out in the go, Data Science is truely a required solution to help future data and to serve well ,making sure it's best justified whenever it is needed.

 

 

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