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Data Analyst vs Data Engineer vs Data Scientist | Data Analytics Masters Program | Edureka - YouTube
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Data has always been Centric
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to any decision making. Today's
world runs completely on data
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and none of today's
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organizations would survive a
day without bytes and megabytes.
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There are several roles
in the industry today
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that deals with data
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and most people have several
misconceptions about them.
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I am Aayushi
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from Edureka and let
me welcome you to this video
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on the key differences
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between three of the leading
roles in data management,
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that are data analyst, data
engineer and data scientist.
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So let's move on and see
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what all we going to cover
in this session first
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and foremost will be starting
by getting a quick introduction
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about the roles as in who is
a data analyst, data engineer
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and a data scientist,
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then we'll be going
through the various skill sets
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that these professionals
possess will also be looking
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at various roles
and responsibilities.
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And finally,
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I'll conclude the session
by telling you guys this is Leo
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what a data analyst
a data engineer
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and a data scientist learn
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so let's begin the session and
start with the very first topic
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who is a data analyst.
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Well a data analyst is the one
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who analyzed all the numeric
and other kinds of data
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and translate it
into the English language
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so that everyone can understand
now this data is used
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by the upper management to make
informed business decisions.
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Now the main responsibilities
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of a data analyst include data
collection correlation analysis
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and Reporting next
is data engineer.
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So a data engineer is the one
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who is involved
in preparing data
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for analytics calor
operational users.
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So these are the ones
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who develops constructs test
and maintain the complete
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architecture of the large
scale processing system.
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Now a typical data ingenious,
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they include building
data pipelines to put
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all the information together
from different sources.
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They then integrated
Consolidated for the clean
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and structure it
for more analytic 6.
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So this probably varies from
organization to organization.
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Next is a data scientist.
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A data scientist is a one
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who analyze and interpret
complex Digital Data
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for instance statistics
of a website.
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Now a data scientist
is a professional
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who deals with your large amount
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of structured as well
as unstructured data.
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They use their skills
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in statistics programming
machine learning in order
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to create strategic plans
now data scientist
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and data engineer job roles
are quite similar
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but a data scientist is the one
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who has the upper hand or all
the data editor activities
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when it comes
to business related
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decision-making data scientist
have the higher proficiency.
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Now, let's look at the road map
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which correlate these three
job roles to start off
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with most entry level
professionals interested
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in getting into Data related
jobs start off as data analyst.
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So qualifying for this role
is as simple as it gets.
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All you need is
a bachelor's degree
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and good statistical knowledge.
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Well strong technical
skills would be a plus
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and can give you an edge
over most other applicants other
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than this companies expect you
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to understand data handling
modeling and Reporting.
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Along with the strong
understanding of the business
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moving forward the transition
between a data analyst role
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and a data engineer one is
possible in multiple ways.
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You can either acquire
a master's degree
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in a related field
or gather amount of experience
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as a data analyst adding
onto the skills of data analyst
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a data engineer needs to have
a strong technical background
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with the ability to create
an integrated API also need
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to understand data pipelining
and performance optimization.
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The next milestone
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in data Engineers Courier
is becoming a data scientist
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while there are
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several ways in which
a data engineer can transition
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into a data scientist rule
the most seamless one is
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by acquiring enough experience
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and learning the
necessary skills.
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Now these skills include
Advanced statistical analysis
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a complete understanding
of machine learning
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and predictive algorithms
and data conditioning next.
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Let us compare these different
roles on the basis
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of their skills their roles
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and responsibilities
in their day-to-day life
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and finally discuss
the salary perspective first.
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Let us see what are
the different skill sets
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required for data.
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Less data engineer
and data scientists.
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So as discussed a data analyst
primary skill sets revolves
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around data equation handling
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and processing now
an ideal skill set
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for this profile would include
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data warehousing Adobe
and Google analytics.
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Then you must have
programming knowledge scripting
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and statistical skills reporting
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and data visualization using
various tools database knowledge
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like SQL or anything
and spreadsheet knowledge.
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Well a beginner's
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level programming experience
would also Aid
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in building better
statistical models as well.
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Now a data engineer
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on the other hand requires
intermediate level understanding
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of programming to build
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our algorithms along
with a Mastery of statistics
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and math most companies hiring
for data Engineers.
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Look for skills,
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like data warehousing and ETL
or you can say extract
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transform load then it has some
Advanced programming knowledge.
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Also Hadoop based analytics
plays a vital role then they
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must have in-depth knowledge
of databases data architecture
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and various machine learning
concept or you can say
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algorithms knowledge fine.
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Any a data scientist
needs to be master
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of both the world's data starts
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and math along with in-depth
programming knowledge
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of machine learning
and deep learning.
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Well the job description
for an ideal data scientist
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include statistical
and analytical skills.
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Then you have
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various data mining
activities machine learning
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and deep learning principles,
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or you can also add up
to its various algorithms.
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Then a data scientist
should also have in-depth
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programming knowledge or you
can see such as in SAS are
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or python languages now
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that you have
a complete understanding of
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what skill sets.
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You need to become
a data analyst
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a data engineer or a scientist.
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Let's look at what
are the typical roles
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and responsibilities of these
professionals now the roles
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and responsibilities
of a data analyst data engineer
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and the data scientists
are quite similar
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as you can see
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from the slides now a typical
data analyst is responsible
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for statistical analysis
and data interpretation.
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They should also
be well familiarized
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with various data reporting
and visualization tools.
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For example, if I
working on python,
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you should know
the various python libraries
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like matplotlib see zbornak.
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Job, and similarly.
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If you are familiar
with our language,
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then you should go for ggplot or
any other visualization library.
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Then a data analyst should
never compromise on the quality.
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This should also be
very friendly with data.
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It works for example
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data equation maintenance
pattern detection data cleaning
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and things like that.
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Next comes to data engineer
well adding onto the work
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of data analyst a data engineer
also maintains the architecture
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the development of it
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and testing of
that architecture.
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So it basically involves
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developing data sets using
machine learning techniques,
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or you can say a data engineer
should also know
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how to deploy
these machine learning
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and deep learning models
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and all the other tasks
assigned with them.
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So for example,
predictive modeling searching
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for hidden patterns
and similar tasks,
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then comes your data scientist.
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Now a data scientist
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on the other hand
is responsible for a lot
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of tasks is responsible
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for mining of data then
develop operational models.
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Then a data scientist
should also be explored
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in machine learning
and deep learning techniques.
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You should also be scale
in data enhancement
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and sourcing method
These another important aspect
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of being a data scientist
strategy planning
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and data integration.
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Now a lesser-known task
of a data scientist is impulsive
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or you can say
or ad hoc analysis
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and finally a data scientist
must be skilled
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at anomaly detection
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and performance tracking now
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after these two
interested topics.
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Let's now look at
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how much you can earn
by getting into a career
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in data analytics data
engineering or data science.
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Now as you can see
the typical salary
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of a data analyst is just
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under fifty nine thousand
dollars per year there
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as a data engineer can earn
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up to ninety thousand eight
hundred and thirty nine
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dollars per year.
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Whereas a data scientist
can earn up to ninety
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one thousand four hundred
seventy dollars per year.
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So isn't this amazing guys now
looking at these figures
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of a data engineer
and a data scientist,
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you might not see
much difference at first
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but delving deeper
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into the numbers
a data scientist can earn
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twenty to thirty percent more
than an average data engineer.
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Also, it's been proven
by various job
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posting from companies
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like Facebook IBM That
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basically coat salaries up to
one thirty six thousand dollars
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per year now taking
this into consideration.
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We also have an expert created
data science master's program
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where you can find
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all the necessary details
to become a radar scientist.
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It include 12 courses
were 250 Plus hours
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of Interactive Learning
along with the Capstone project.
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You can find out all
the details curriculum
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that timings everything
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over here and let me also tell
you one more thing guys.
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You will also be awarded
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with an industry-recognized
certificate in the end.
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So do check out this page guys.
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I will drop the link
in the description box below.
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Well, that's all for today.
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I hope you guys
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like this session have
a lovely weekend.
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Enjoy.
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Bye.
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Thank you.
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I hope you have enjoyed
listening to this video.
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Please be kind enough to like it
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and you can comment any
of your doubts and queries
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and we will reply them
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at the earliest do look out
for more videos in our playlist
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And subscribe to Edureka channel to learn more.
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Happy learning.
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