Data Analyst vs Data Engineer vs Data Scientist | Data Analytics Masters Program | Edureka

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

20 thoughts on “Data Analyst vs Data Engineer vs Data Scientist | Data Analytics Masters Program | Edureka

  1. Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Data Analytics Course Curriculum, Visit our Website:

  2. Nice said $91000 yearly package for Data Scientist..please correct me if I am wrong…if I convert in INR then package shows approx 64 Lakhs yearly…is it correct?

  3. Data Scientist is not necessarily a progression from Data Engineer career path. They are different, but complementary roles, both required for productionalized analytics.

  4. I have completed bcom and i dont know much about computer languages can i do data analyst and please do tell me do i need to learn any computer languages before doing data analyst if yes then please tell me what computer languages i have to learn and what are the other things i have to know before doing data analyst?

  5. Government Agencies and Private Corporations don't have neither resources nor budgets to hire DS, DE, and DA to address Data Analytical Studies in their IT Departments. A well qualified Systems Analyst with Programming experience coupled with specific know-how of Domain (Example Oil Industry or Healthcare) should be able to address the roles of DS, DE, and DA successfully.

  6. Nice overview. At my company I have to do some tasks from all 3 areas. I susuppose most companies want single person to be able to do all these tasks.

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