hey guys welcome to this comparative
analysis session by Intellipaat in this
session we are going to compare and
contrast data scientists and data
analysts in this data-driven world we
need valuable information to make a
business successful to obtain that
information we need data scientists and
data analysts so in this session we'll
be comparing them now before moving on
to this session please subscribe to our
channel so that you don't miss our
upcoming videos now let's take a quick
glance at the agenda so we'll start off
by learning the need for data after that
we'll be looking into what a data
scientist does move ahead we'll be
learning what data analyst actually does
after that we'll be looking into the
skill set of a data scientist versus a
data analyst and finally we'll be
learning about the future scope and
salary of data scientist as well as a
data analyst now without any further
delays let's begin with the session
starting with why do we need to handle
data so you'll understand the need of
handling data with the help of an
example
a real-life example of Google Maps so
you all must have used Google Maps in
your day-to-day lives for traveling from
one place to another
for knowing the destination for knowing
the route for the destination the
distance the time that you would require
to reach the destination also this
Google Maps shows us the transportation
system it gives us the fare for
different transports different modes of
transports so it is a wonderful
application of data science and machine
learning that helps us in our day-to-day
lives so how do this application
predicts so accurately so this is all
with the help of real-time data so you
can understand that how important data
is so if you have an Android phone or an
iPhone with Google Maps open and
services enabled on it then your phone
or the application sends real-time data
back to Google then Google uses this
information or data to calculate how
many cars or vehicles
they're on the road and how fast they
are moving so as more number of people
start using this app the traffic becomes
more accurate Google also collects the
data of traffic from various
applications that monitors the traffic
reports from the local Department of
Transportation then it also keeps a
history of traffic patterns on a
specific road so that it can predict the
traffic at a specific time and on a
specific location so this application
majorly uses data rely on data to show
us the best results it can so Google
Maps suggests a faster route to reach
our destination on time if the traffic
is more so it uses real-time location if
you are feeling like Google is
monitoring and tracking your every move
then you can opt out anytime by turning
off the location services but what if
everyone did that well Google would be
in trouble then as the data and the
result might not be accurate and this is
the reason why at some places where
Google Maps is not so accurate so the
world all it revolves around data which
helps us to get the experience of such
wonderful applications now who is a data
analyst so going on to the definition of
data analysis so data analysis is a
process of inspecting cleansing
transforming and modeling data with the
goal of discovering useful information
from it informing conclusions and
supporting decision making basically
data analysts collect process and
perform statistical analysis of the data
and their skills may not be as advanced
as data scientists but their goals are
saying to discover how data can be used
to answer the questions and solve
problems so a data analyst job is to
take the data and use it to help
companies make better business decisions
this could mean figuring how to price a
new material for the market how to
reduce transportation cost solve issues
that cost the company so a data analyst
basically looks at some data and try to
make sense out of it so for example if
sales are going down so what do you do
you check through the - boots or query
data from your database using sequel and
find out which category suffered the
most then going deeper and find out
other factors is the task of a data
analyst they perform analytics on the
data to know what is going on and then
talks to the product manager with the
evidence through how to fix that problem
so this is majorly the task of a data
analyst ok guys a quick info intellipaat
provides an end-to-end training on data
science with R and Python and if you're
looking for it you can check out the
details in the description now let's
continue with this session now we'll
look at the roles and responsibilities
starting with designing and maintaining
the data systems so they collaborate
with the data engineers to design the
architecture that efficiently helps them
to fetch the data and the information
from the database then mining data from
primary and secondary resources for the
organization and they extract relevant
information or relevant data for the
organization then using statistical
tools to interpret data set they perform
statistical analysis on the data to
analyze the data then analyzing and
visualizing the data are the majorly one
of the important tasks of a data analyst
then finding trends and patterns in the
data to know the insights of the data
then preparing reports that effectively
shows the trends patterns and
predictions using the data then
implementing business analytics to
understand and optimize the business by
making effective strategies then
collaborating with programmers may be
they can be machine learning engineers
data engineers or data scientist or
software developers to make them
understand the business requirements
then recommend system modifications and
improvements by analyzing all the
conditions and situations of the
business and develop policies for
now moving on to the next part we look
at who is a data scientist so going on
to the definition a data scientist as a
professional hook extensively works with
large data sets in order to derive
valuable business insights from it so
data science is basically an
interdisciplinary field that uses
scientific methods processes algorithms
and systems to extract knowledge and
insight from many structural and
unstructured data so the field of data
science is majorly related to data
mining machine learning deep learning
big data and artificial intelligence so
talking about data scientist so data
scientists are big data Wranglers and
gathering whose task is to gather and
analyze large sets of data that can be
structured or unstructured so data
scientists role combines computer
science statistics and mathematics
majorly they analyze and process the
model they model the data then interpret
the results to create actionable plans
for companies and other organizations
and also data scientists are analytical
experts who utilize their skills in both
technology and social science to find
trends and manage data they reuse
industry knowledge contextual
understanding skepticism of existing
assumptions to uncover solutions to
business challenges and a data scientist
work typically involves making sense of
messy and unstructured data from various
sources such as smart devices social
media fields and emails that don't
neatly fit into a database so data
scientists are the game changers so all
the applications all the interesting
applications such as Google Maps or
recommendation systems of various
websites that you can see these all are
applications of data science and these
are created by data scientists so now
we'll look at the roles and
responsibilities of data scientists so
starting with collecting large amounts
of data and analyzing it there
using data-driven techniques for solving
business problems then communicating the
results to business and IT leaders
spotting the trends patterns and
relationships within the data then
converting the data into compelling
visualizations so that they can
understand the trends and behavior of
the business where it is going then
deals with the client for gathering
requirements for the business designing
algorithms for machine learning models
so they collect the data from various
sources or maybe from data analysts and
look into the data in the context of
creating machine learning or automated
model using various machine learning
algorithms then they are also involved
in deploying machine learning models
with the help of machine learning
engineers and they are involved in the
task of iteratively improving the model
by providing them the quality data that
the model needs to learn and working
with artificial intelligence and machine
learning techniques are the basic and
very important role of a data scientist
ok guys a quick info Intellipaat
provides an end-to-end training on data
science with R and Python and if you're
looking for it you can check out the
details in the description now let's
continue with this session now we
understand difference between a data
analyst and a data scientist so starting
with data analyst so we already know
data analyst collect data from various
sources or they can be primary or they
can be secondary sources they pre
process the data they clean the data
manipulate and also visualize the data
the performance data big data analytics
on the data they create reports then a
data scientist collects the data
collects the analyze data and looks it
with an angle of creating such a process
that helps in building automated models
that helps in the prediction for the
business and also the task of a data
scientist is to analyze and visualize
the data and decide about which
algorithm should be used so this is
the major difference between a data
analyst and a data scientist now moving
on to the next part that is we will look
into the skill set of data scientist and
data analyst starting with data
scientist so a data scientist should
have knowledge of sequel that is will
structured query language used for
databases then tableau or power bi that
is used for data visualizations so they
must have knowledge of these two tools
in Microsoft Excel then going to the
programming languages they should have a
comprehensive knowledge of Python as
well as R so there are various libraries
in Python and R both various libraries
and packages that are specifically used
in data science machine learning and
artificial intelligence to analyzing and
visualize the data to create machine
learning models create automated models
so they should have knowledge of both
these languages then mathematics a data
scientist must have a thorough knowledge
of mathematics especially statistics and
probability linear algebra calculus
differential equations because these are
used for creating machine learning
models then data pre-processing
manipulation and visualization these are
the basic tasks of a data scientist so
they should be thought of with data
pre-processing manipulation and
visualization tasks then machine
learning algorithms so there should be
an expert and in implementing various
machine learning algorithms on the data
sets so that they can create models
predictive models out of that then they
should have knowledge of artificial
intelligence which includes neural
networks and deep learning the knowledge
of neural networks and deep learning is
very important for a data scientist to
know then obviously software engineering
they should have knowledge of software
engineering as to build work on various
softwares creative softwares then
finally they should be a good problem
solver
now moving on to the next part that is
skills of a data analyst so they also
should have knowledge of sequel that is
structured query language then tableau
that is used for data visualization and
Microsoft Excel then programming
languages they should have knowledge of
Python or R that is used for that is
used by data analysts to perform various
analytics techniques then statistical
knowledge is must for a data analyst as
statistics is used for analyzing the
data and applying statistical techniques
to understand the insights of the data
then a data analyst should also be a
good problem solver to analyze the
business problems to solve the business
problems and make effective strategies
for increasing the revenue generation of
our business then ability to analyze
model and interpret the data then they
should also have knowledge basic
knowledge of data science then machine
learning algorithms so that they can
collaborate with data scientist and ml
engineers for building predictive models
then comes creating dashboards and
reports for the organization so that
everyone can understand about the trends
and patterns of the business data to
know the insights of the data and to
understand in which direction the
business is actually going now we will
see the jpb scope and salary of data
analyst and a data scientist so starting
with data analyst
according to Forbes in India there are
5000 plus jobs available for a data
analyst in 2020 and talking about United
States the number of jobs are more than
12,000 so you can see there are a
plethora of career opportunities in the
field of data analytics talking about
average salary so in India the average
salary of a data analyst is 7 lakh
50,000 per annum and in the United
States it is dollar 1 lakh 15,000 and 5
then moving on to the data scientists
talking about number of jobs according
to Forbes in India there are 10,000 plus
jobs available for a data scientist in
2020 and in the United States the number
of jobs are more than 25,000 so there is
a wide scope of opportunity in data
science field also so people who are
willing to become a data scientist
so there are plethora of opportunities
that you can wrap so talking about
average salary a data scientist earn an
average salary of 9 lakh 35,000 in India
and in the United States it is dollar 1
lakh 32,000 in this video we understood
why we need to handle data what is the
importance of data with the help of the
example of Google Maps then we looked
into the roles and responsibilities of
data analyst and data scientist then
what are the skill set that makes a data
scientist and data analyst after that we
understood the difference between a data
scientist and data analyst and finally
we looked into the job scope and salary
of both these profiles so this is all
you need to know about the difference
between a data analyst and a data
scientist ok guys a quick info
Intellipaat provides an end-to-end training
on data science with R and Python and if
you are looking for it you can check out
the details in the description ok guys
we've come to the end of this session I
hope this session was helpful and
informative for you if you have any
doubts or comments you can leave that in
the comment section below and we allow
to help you out thank you
