 |
| Introduction to data science |
What is Data Science in simple?
In simple words, Data Science is a study of data. It is helpful to take effective decisions for business growth.
How data is
divided in Data Science?
Data is real and it is divided into two types namely
structured data and unstructured data.
Structured Data: You might observe data in rows &
columns (Ms. Excel) i.e. data in a tabular format.
Eg: Student exam result data, class attendance list, etc.
Un-Structured Data: Data that is not structured,
it means data doesn’t arrange properly (Understandably).
Eg: Audio, Video, Weblogs, and Images, etc.
How should companies get started in Data Science?
Every company must collect and save the data first. If
you are not yet collecting data, then start saving the data now. Also, if you
are already having old data then, don’t overwrite it. Archive it. Because data
doesn’t get old. Data is real. If data exists then only you can able to apply
different algorithms. Also, one data scientist is not enough and a team
required.
Recruiting for
data science:
If you are really passionate about data science, you
must be good at curiosity like, for instance, if you enter a new room you
should be curious about things and you should observe how good paintings are
and what are all the books present in a book self, etc? So, I can say that along
with technical skills, you should be good at curiosity and have a good sense of
humor.
An HR will look into how much curious you are and have a
sense of humor first. If you are good at these things then he will analyze the
technical background in you. Also, if there is a sign of good thinking and easy
learning skills in you, mostly he will recruit you.
Curiosity is not trainable, it should come in you and you have to analyze things. Also, you should be good at storytelling, visualization. The tools for data science are R, Python, Scala, etc.
Applications of Data Science:
Data Science is widely used in multiple areas. Like, in
medical, Automobile, Educational, etc.
Speech Recognition, Google search, Image Recognition, etc
Let me make it more clear to you by taking an
example.
A girl named Laura went shopping and she returned home after few hours. She started receiving emails and messages related to
pregnancy. Her father complained against these messages and notifications to
the shopping mall. But, after two weeks he came back to the shopping mall and
he conveyed apologies to them and he explained that he didn’t know that her daughter
Laura is pregnant. But, how they knew before?
Well, she shopped some of the vitamin tablets &
some stuff related to pre-pregnancy and based on these notifications, emails or
messages were sent. This is data science.
Click Here To Enroll- Free Course