The Ultimate Guide to a Career in Data Analytics: Roles, Responsibilities, and Skills
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Introduction
In today’s digital landscape, the demand for data analysts is soaring as companies recognize the importance of data-driven decision-making. This comprehensive guide explores the various facets of a career in data analytics, highlighting job roles, responsibilities, necessary skills, and potential salaries. Whether you’re looking to dive into this exciting field or simply want to upgrade your current skill set, this article serves as a definitive roadmap.
Understanding Data Analytics
Data analytics involves the systematic computational analysis of data. It transforms raw data into meaningful insights, enabling organizations to make informed decisions. Here’s a closer look at what data analytics encompasses:
Key Components of Data Analytics
- Data Collection: Gathering data from various sources, such as surveys, transactions, and APIs.
- Data Cleaning: Processing data to remove inconsistencies and erroneous entries.
- Data Analysis: Employing statistical methods to analyze the data and uncover patterns.
- Data Visualization: Presenting data insights through graphical representations to facilitate understanding.
- Decision Making: Applying analytical findings to inform business strategies.
Career Opportunities in Data Analytics
Data analytics offers a multitude of career paths. Here are some of the key roles you may encounter:
1. Data Analyst
Responsibilities:
- Collecting and analyzing data to identify trends.
- Creating data visualizations and reports for stakeholders.
- Collaborating with other teams to solve business problems.
Skills Required:
- Proficiency in SQL, Python, or R.
- Familiarity with tools like Excel, Tableau, and Power BI.
- Strong statistical analysis skills.
Average Salary:
- India: ₹5,23,000 per annum
- United States: $62,400 per annum
2. Business Analyst
Responsibilities:
- Evaluating business processes and identifying areas for improvement.
- Communicating with stakeholders to gather requirements and insights.
- Delivering data-driven recommendations to enhance efficiency.
Skills Required:
- Knowledge of programming languages such as R or Python.
- Proficiency in SQL and data visualization tools.
- Strong analytical and critical thinking abilities.
Average Salary:
- India: ₹7,00,000 per annum
- United States: $68,446 per annum
3. Data Scientist
Responsibilities:
- Building predictive models using machine learning algorithms.
- Performing data mining to extract necessary data from large datasets.
- Analyzing the business impact of various data-driven decisions.
Skills Required:
- Strong programming skills (Python, R, Java).
- Knowledge of machine learning and statistical modeling.
- Experience with data visualization libraries.
Average Salary:
- India: ₹10,47,000 per annum
- United States: $113,000 per annum
4. Data Engineer
Responsibilities:
- Designing data pipelines and architecture.
- Managing and optimizing database systems for analysis.
- Working closely with data analysts and scientists to manage data flows.
Skills Required:
- Proficiency in big data technologies (e.g., Hadoop, Spark).
- Strong programming skills (Python, Java).
- Understanding of SQL and NoSQL databases.
Average Salary:
- India: ₹8,85,000 per annum
- United States: $103,000 per annum
5. Machine Learning Engineer
Responsibilities:
- Developing algorithms that allow systems to make predictions.
- Collaborating with data analysts and scientists to refine models.
- Implementing solutions to enhance model accuracy.
Skills Required:
- Expertise in machine learning algorithms.
- Strong programming skills (Python, R).
- Familiarity with software development practices.
Average Salary:
- India: ₹8,00,000 per annum
- United States: $114,000 per annum
Skills Needed for a Data Analyst Career
To thrive in a data analytics career, you need a blend of technical, analytical, and soft skills:
Technical Skills
- Statistical Knowledge: Strong understanding of statistical tools and techniques.
- Programming Expertise: Proficiency in Python, R, or SQL for data manipulation and analysis.
- Data Visualization: Ability to visualize data effectively using tools like Tableau and Power BI.
Analytical Skills
- Critical Thinking: Ability to analyze data and derive actionable insights.
- Problem-Solving: Aptitude for identifying data-related challenges and proposing solutions.
Soft Skills
- Communication: Strong verbal and written skills to present findings to stakeholders.
- Collaboration: Ability to work effectively in teams and with various departments.
Data Analytics Certifications
Pursuing certifications can significantly boost your employability and expertise:
- Certified Analytics Professional (CAP)
- Google Data Analytics Professional Certificate
- IBM Data Analyst Professional Certificate
- Microsoft Certified: Data Analyst Associate
- Tableau Desktop Specialist
Salary Ranges in Data Analytics
Data analytics salaries vary greatly by role, location, and experience. Typically, entry-level positions start around ₹5,00,000 to ₹8,00,000 in India and $60,000 to $70,000 in the U.S. With experience, salaries can increase substantially:
- Mid-Level Data Analyst:
- India: ₹10,00,000 - ₹12,00,000
- U.S.: $80,000 - $100,000
- Senior Data Analyst:
- India: ₹15,00,000 and above
- U.S.: $120,000 and above
Conclusion
A career in data analytics is not only rewarding financially but also offers an opportunity to make meaningful contributions to organizations. By acquiring the relevant skills and certifications, and understanding the various roles in this field, you can set yourself on a path to success. Continuous learning and adaptation to technological advancements will further enhance your prospects in the ever-evolving landscape of data analytics.
hey everyone welcome to Simply Lo in today's session we will go through the data analyst fil course but before we
begin if you are a tech gek in a continuous hunt for latest technological Trends then consider getting subscribed
to our YouTube channel and don't forget to hit that Bell icon to never miss an update from Simply now without further
Ado let's go through the agenda for today's session first we will get started by getting a brief understanding
of data analytics as a carrier job roles and responsibilities and salary descriptions and followed by that we
will go through a detail data analyst road map then to add up we will go through some important top
certifications for data analyst and we will understand the fundamental differences between a data analyst and a
data scientist followed by that we will have the data analytics Basics Next we will deep dipe into oap and olp and also
understand the differences between them then we will get started with the practical demonstration by understanding
the ATL pipeline then the top 10 data analyst tools and followed by that we will get through the msxl for data
analytics time series analysis and then data analytics with python and data analytics with SQL followed by that we
will go through some of the most important data visualization tools which as powerbi and W and we will also use
some of the most important data sets for the use cases and finally to make things more interesting we will also go through
some of the most frequently Asked data anal itics interview questions in real time I hope I made myself clear with the
description to FasTrack your Ambitions whether you're making a switch or aiming higher simply learn has your
back and if you're an aspiring data analyst try giving a sh to Simply learns postgraduate program in data analytics
from P University in collaboration with IBM the link in the description box and the pin comment should take you to the
programing off it with that over to our training experts hello everyone we have an interesting topic for today and that
is data analytics jobs career and salary I will run you through the top six data analytics job roles so before I dive
deep into the various job roles let's quickly understand how important a career in data analytics is and what the
data so back in the early 2000s there was relatively less data generated but with a rapid rise in Technologies and
with the increase in the number of various social media platforms and multinational companies across the globe
the generation of data has increased by Leaps and Bounds did you know that according to the IDC the total volume of
data is expected to reach 175 zettabytes in 2025 now the that's a lot of data let's
take a look at how organizations leverage all of this data as you know there are zillions of
companies across the world these companies generate loads of data on a daily basis when I say data here it
simply refers to business information customer Data customer feedback product Innovations sales reports and profit
loss reports to name a few companies utilize all of this data in a wise way they use all of this
information to make crucial decisions that can either hamper or boost their businesses you might have heard of the
term data is the new oil well it definitely is but only if organizations analyze all the available data very well
then this oil is definitely valuable and for that we have data analytics organizations take the help of
data analytics to convert the available draw data into meaningful insights so what is data analytics
technically you can say it is a process wherein data is collected from various sources then cleaned which involves
removing irrelevant information and then finally transformed into some meaningful information that can be interpreted by
humans various Technologies tools and Frameworks are used in the analysis process as you might have heard of the
term data never sleeps well it surely doesn't every millisecond some of the other data is generated and this is a
constant process this process is only going to increase in the near future with the Advent of newer Technologies
the data analytics domain holds Paramount importance in every sector companies want to leverage on all the
generated big data and boost their businesses they need professionals who can play with data and convert them into
crucial insights organizations are constantly on the lookout for such candidates and this opportunity will
only increase as data is only going to grow every second so if you want to start your career in
this field or if you want to switch your job role into a role in the data analytics domain then we have a set of
job profiles that you can look at we will look into six job roles in the data analytics fields and learn what
each job role is all about the responsibilities of a professional working in that particular role the
skills required to get that particular job the average annual salary of a professional working in that rooll and
finally the company's hiring for that rooll so let's start off first we have the job role of a data analyst a data
analyst is a person who collects processes and performs statistical analysis of large data sets every
business generates and collects data be it marketing research sales figures Logistics or Transportation costs a data
analyst will take this data and figure out a variety of measures such as how to price new materials how to reduce
Transportation costs or how to deal with issues that cost the company money they deal with data handling data modeling
and Reporting now talking about their responsibilities data analysts recognize and understand the organization's goal
they collaborate with different team members such as programmers business analysts engineers and data scientists
databases they filter and clean data using different modern tools and techniques and make it ready for
analysis they also perform data mining from primary and secondary data sources data analysts identify analyze
and interpret Trends in complex data sets this is done using statistical tools such as R and SAS
another key responsibility of a data analyst is to create summary reports and build various data visualizations for
decision-making and presenting it to the stakeholders next let us discuss the important skills that you need to know
to become a data analyst firstly you should have a bachelor's degree in computer science or
information technology a master's degree in computer applications or statistics is also
preferable you must have a good understanding of of programming languages like R python JavaScript and
also understand SQL in addition to that it is beneficial if you have hands-on experience with
statistical and data analytics tools such as SAS Miner Microsoft Excel and ssas basic understanding of machine
learning and its algorithms would be an advantage acquaint yourself with descriptive predictive prescriptive and
various data visualization software along with presentation skills this will help you pitch in your ideas and
a data analyst earns nearly 5 lak 23,000 rupees perom in India while in the United States they earn around
$62,400 per anim let's now look at a few of the companies hiring data analysts so as you
can see we have the American e-commerce giant Amazon then we have Microsoft the American online payment company PayPal
then we have Walmart Bloomberg and capital 1 so that was all about data analyst the next job role is of a
services and software through datadriven solutions they are responsible for Bridging the Gap between it and and
business using data analytics to evaluate processes determine requirements and deliver datadriven
responsible for creating new models that support business decisions and come up with initiatives and strategies to
analyst business analysts have a good understanding of the requ requirements for business their vital role is to work
in accordance with relevant project stakeholders to understand their requirements and translate them into
details which the developers can understand they frequently interact with developers and come up with a plan to
design the layout of a software application they also run meetings with stakeholders and other authorities they
engage with Business Leaders and users to understand how datadriven changes to products services
software and Hardware can improve efficiencies and add value they ensure that the project is
running smoothly as per the requirements and the design planned through user acceptance and validation
testing they make sure all the features are being incorporated into the application Bas rely on different
software to write documentation and design visualization to explain all the findings it is extremely critical for
any ba to effective L document the findings where each requirement of the client is mentioned in
detail now let us look at the skills required for a ba a bachelor's degree in the field of science engineering or
statistics or any related domain will suffice knowledge of programming languages such as Python and Java is
beneficial you should be really good at writing complex SQL queries and you should also have knowledge of various
analytical and problem solving skills are necessary to solve software and business issues you also need to have
excellent presentation and communication skills both oral and written moving on to their salary a
business analyst is expected to earn around 7 lakh rupees perom in India in the US they earn nearly 68,4 $46
perom IIA Dell Phillips Honeywell the famous American messaging platform WhatsApp the UK based company Ernest and
administrator who maintains a successful database environment by directing or performing all related activities to
keep keep the organization's data secure they are responsible for storing organizing and retrieving data from
several databases and data warehouses their top responsibility is to maintain data Integrity this means
maintains a database to ensure that the the data in it is properly stored organized and managed well they maintain
data Integrity by avoiding unauthorized taxes and they keep databases up to date they run tests and modify the existing
databases to ensure that they operate reliably they also inform end users of changes in databases and train them to
responsible for taking system backups in case of power outages and other disasters so they should have an
efficient Disaster Recovery plan now let's have a look at their skills to become a database
administrator you should have a bachelor's degree in computer science or information technology knowledge of
programming languages such as python Java and Scala is important you need you need to carry at
least 3 to 5 years of experience in data management you need to have an understanding of different databases
such as Oracle DB mongod DB MySQL server and pogress SQL also they should have an idea about database design and writing
SQL queries finally you need to have a good understanding of operating systems such as Windows Mac OS and Linux along
earn up to 4ak 97,000 rupees perom in the US they earn around $78,000 perom let's have a look at the
companies's hiring for database administrators so as you see here we have bookm show Oracle the American MNC
Intel Amazon Robert Half and the New York Times to name a few fourth in the list of job roles we
have data engineer a data engineer is someone who's involved in prep comping data for analytical and operational uses
a data engineer transforms data into useful format for analysis they build and test scalable Big Data ecosystems
scientist now let's jump into their responsibilities data Engineers develop test and maintain architectures they are
responsible for managing optimizing and monitoring data retrievals to storage and distribution throughout the
organization they discover opportunities for data acquisition find Trends and data sets and develop algorithms to help
make raw data more useful to the Enterprise data engineers build large data warehouses using ETL for storing
and retrieving data they also recommend ways to improve data quality and efficiency along with
building algorithms to help give easier access to Raw data data engineers often work with big
data and submit their reports to data scientists for analysis purpose they need to recommend and sometimes
Implement ways to improve data reliability efficiency and quality moving on to the skills of a data
engineer a data engineer should hold a bachelor's degree in computer science or information
technology they should have good hands-on experience with python R and Java also data Engineers should be well
wored with big data technology such as Hadoop Apache spark Scala Cassandra and mongodb data warehousing and detail
experience are essential to this position along with in-depth knowledge of SQL and other database
Solutions basic knowledge of statistical analysis will be an advantage along with idea about operating
systems here is what a data engineer can earn so in India a data engineer can earn up to 8 lakh 85,000 rupes per anim
professional who uses statistical methods data analysis techniques machine learning and related Concepts in order
to understand and analyze data to draw business conclusions they make sense to messy and unstructured data and bring
value out of it they employ techniques and theories drawn from many fields within the context of mathematics
challenges in business and comes up with the best Solutions using modern tools and techniques to analyze visualize and
build prediction models to make business decisions let us now look at their responsibilities in the
industries data scientists clean process and manipulate data using several data analytics tools they perform adhoc data
mining collect large sets of structured and unstructured data from disparate sources they design and evaluate
Advanced statistical models to work on Big Data they also create automated anomaly detection systems and keep
constant track of their performance data scientists interpret the analysis of big data to discover
dashboards for Relevant stakeholders they also adopt new business models and approaches apart from this they
regularly built predictive models and machine learning algorithms now moving on to the skills
technology will be fine but a master's degree in the field of data science will hold a major advantage you also need to
have a good experience in the analytics domain you should be proficient in programming languages such as python
Hadoop in addition to knowing programming languages you also need to know SQL machine learning and deep
learning data visualization and bi skills are necessary for creating reports and dashboards you should also
be able to communicate and present information and ideas properly now talking about their salary
a data scientist in India can expect an annual salary of 10 lakh 47,000 rupees per year meanwhile in the US they can
data scientists here we have a few companies named they are yet again Amazon City Bank Apple Google the
Japanese electronic Commerce and online retailing company rakuin and Facebook and finally we have machine
learning engineer machine learning Engineers are professionals who develop intelligent machines that can learn from
algorithms and statistical modeling to make sense of data they design and develop machine learning and deep
learning algorithms their main goal is to create self-running software let's have a look at the
design and develop machine Learning Systems they use exceptional mathematical skills in order to perform
faster computations and work with algorithms to create sophisticated models they perform AB testing and use
data modeling to fine-tune the results they use data modeling and evaluation strategy to find hidden
patterns and predict unseen instances machine learning Engineers work closely with data Engineers to
build data pipelines and interact with stakeholders to get a Clarity on the requirements most importantly they
analyze complex data sets to verify data quality perform model tests and experiments choose to implement the
right machine learning algorithm and select the right training data sets moving on to their
skills a machine learning engineer should have a degree in computer science and information technology they should
have an advanced degree in computer science or maths in addition to this they should also have experience in the
C++ and Java knowledge of Statistics probability and linear algebra is necessary as all the machine learning
algorithms have been derived from mathematics also having an idea of signal processing would be
beneficial machine learning Engineers need to have a good understanding of data manipulation and machine learning
libraries such as numai Panda psyit lar Etc they should have good oral and written communication skills let us now
have a look at their salary structure a machine learning engineer earns $8 lakh rupees perom in India while in the US
it let's have a look at the company's hiring machine learning engineers so as you see we have Amazon Microsoft
Oracle Salesforce Rapido and Accenture to name a few that was all about the job role of a machine learning
engineer now that we have seen the different job roles in the field of data analytics let's also go ahead and see
resume of a data analyst you you can grab some ideas from this and incorporate them in your resume nowadays
it's quite common to have a professional photograph of yours on the resume you can go ahead and have that then your
name in bold followed by your contact details like email ID and phone number then moving on you would have to
write a summary briefly explain your current job role and what you're looking for in the future having a LinkedIn
profile link works well these days employers can just go ahead and look at your profile and gauge you well make
sure to have an active LinkedIn profile in addition to LinkedIn profile it's also good to have a GitHub profile link
which can show your coding or other technical skills if it's impressive enough then a lot of times the rest of
your resume is just secondary as I mentioned this is a resume of a data analyst so as you can
see in the summary here we have just spoken about the basic responsibilities of a data analyst
moving on to the experience part you have to write the job title and below that you can mention the company and the
tenure accordingly here you would have to give a brief description of achievements in the organization any
relevant accomplishments related to the job you're applying for the tools and the various Technologies you have worked
with so in the sample you can see we have spoken about data visualization using RN tblo next we have spoken about
how the candidate has worked with other teams for a Better Business outcome most of the data an lists use SQL and
Excel to handle data for reporting and database maintenance and we have mentioned that here as well do make sure
that you always specify the tools you use then you can also mention if you have worked on improving data delivery
for example here we have spoken about developing and optimizing SQL queries data aggregations and ETL to improve
becoming a data analyst here we have taken the role of a statistical assistant as the first job since it's
easier for a candidate with this job role to shift into the data analytics field nevertheless you all can still
mention your prior experience here be it in any domain under the responsibilities for this job role we have given Basics
such as coding data prior to computer entry compiling statistics from VAR ious reports Computing and analyzing data and
finally some visualization and Reporting moving to the education here you can mention the name of your degree
and the university name if you have a postgraduation well and good you can list both the degrees here also if you
have any certifications you can mention them here under the education category now moving to the skills
depending on your skills and your choice you can either shift this part to the beginning of the resume or have it
here as you see on your screens this is just a different way of displaying your skill sets you can have all the five
stars colored if you are excellent in that particular tool or language as you see it's crystal clear
as to what the candidates strong areas are you can have various categories like shown for example under software
development you can list the languages that you know and how proficient you are in those particular
languages it's clear that the C Val knows python better than JavaScript here so the employer gets a clear idea about
the skills you possess and the depth of it similarly you can mention the databases as well the few mentioned here
are more or less a requirement to become a data analyst at least SQL is a must not to forget data visualization is
also very important when it comes to the job role of a data analyst mention the tools you know here and similarly give
yourself a rating out of five five stars shaded being the highest here we have mentioned Tableau and Excel which are
more than sufficient to become a data analyst moving to the non-technical skills you can mention the languages you
know here here we have taken English and German in addition to the languages you can also feel free to mention the
data analyst should look like you can alter it according to your achievements skills skills and experience a study
from new Vantage Partners suggest 97.2% of companies are now investing in data and its analysis nowadays every company
needs a data expert do you also want to become a part of this Market if yes how to become a part of it what are the
essential skills one should have this video will answer all these questions but before watching this video
please subscribe to Simply learns YouTube channel and press the Bell icon to never miss any updates first of all
we are going to discuss who is a data analyst working of a data analyst skills required to become a data analyst tools
required and Company's hiring and finally we are going to discuss about salary of a data analyst let me tell you
how simply learn can help you in your journey to become a data analyst check out the course on data analytics in
collaboration with IBM with realtime project and business case studies you will learn tools like scipi pandas and
programming languages like python or R2 enroll Now link is in the description box below question for you which one of
Jupiter notebook please leave the answer in the comment section below moving on who is a data analyst a data analyst
collects analyzes and interprets data a data analyst will convert raw data into useful information data analyst are in
high demand because every industry users data analysis work of a data analyst as a data analyst you will work closely
with the raw data and generate valuable insights to help companies decide their future goal if you like thinking out of
the box you are the perfect fit for this domain data analyst help maximize output when it comes to generating Revenue
working closely with both business and data nevertheless this field boost handsome salaries for all levels of
expertise can you become a data analyst without prior experience yes anyone can become a data analyst if they enjoy
solving real world problems have a strong background in statistics and have a creative mind if you feel you don't
have it you can definitely develop it so let us know the skills in detail what are the basic skill sets required for a
data analyst data analyst must know basic mathematics and statistics programming skills machine learning and
also data visualization tools so let us know what are the basics that you need to learn as a data
analyst mathematics it is always better to know basic mathematics like linear algebra and probability fundamentals
linear algebra is used in data pre-processing and transformation which is the critical process of every data
analyst statistics a branch of mathematics that deals with collection analysis presentation and
implementation probability we know that probability is the study of how life Lely something will happen which is
essential for concluding both probability and statistics are the backbones of data analysis it is
feasible to become a data analyst with only a basic understanding of these three areas of mathematics but in order
to remain relevant and grow as a data analyst one's mathematical knowledge should not be restricted compulsorily
most Val known spreadsheet software in the world it also has computation and graphick features that are excellent for
data analyst no matter your area of expertise or additional software you might want Excel is a standard in the
industry it's useful buil-in features include form design tools and pivot table it also generate a wide range of
every data analyst should know python it is easy to learn and has a simple syntax python is quite adaptable and includes a
vast variety of resource libraries that are appropriate for a wide range of diverse data analytics activities these
libraries help in numerical and data computation the pandas and numai libraries for instance are excellent for
supporting standard data processing and streamlining highly computational operations you can also choose between
Python or r r is a well-known open Source programming language much like python data visualization tool as we
previously mentioned data visualization tool is also necessary to become a data analyst powerbi is a userfriendly
interface makes building interactive visual reports and dashboard simple its most vital selling point is its superb
data integration it works flawlessly with Cloud sources like Google and Facebook analytics as well as text files
SQL servers and Excel is one of the best commercial data analysis tool available it handles huge
amounts of data better than many other bi tools and is effortless it has a visual drag and drop interface however
because it has no scripting layer there is a limit to what Tableau can do for example it could be better for
MySQL a lot of time it is a standard language for interacting with databases and it is very helpful when working with
structur data SQL creates userfriendly Das PS that may present in various data ways in since it is so simple to send
complex commands to databases and change data in seconds it has commands like add edit delete data in Edition SQL is an
excellent tool for creating data warehouses because of its Simplicity Clarity and interactivity
overall I would suggest that to become a data analyst you should work on programming languages like python or R
plus MySQL to work on databases adding to that Excel plus visualization tools like tblo or powerbi you now know what
to troubleshoot the reporting database environment and reports data analyst you will use statistical method to analyze
data sets and spot any valuable trends that may develop over time evaluate companies functional and non-functional
requirement data analyst assess data warehousing in inspecting and Reporting needs these are all the responsibility
of a data analyst in an organization coming to companies hiring a data analyst IBM accentor capam mini TCS
Facebook Amazon flip cart meta these are the top companies hiring a data analyst but data suggest that every small and
medium-sized company needs a data analyst therefore demand of a data analyst is in every company so there is
no need to worry job and salary of a data analyst this is the final part the salary of a data analyst is high all
over the world when it comes to the USA the average salary for a data analyst as a beginner is going as high as 70,000
plus per anom for experienced professional it is going as high as $120,000 perom in India for a fresher it
is going as high as 8 lakh perom and for experienced professionals it is 20 lakh plus perom such as the demand for data
analyst now that we have covered every important skill it's time for you to start working on it certifications have
become an essential Benchmark for professional growth and recognition in the dynamic field of data analytics they
not only validate your expertise but also open doors to exciting new career opportunities and when it comes to topn
certifications simply learns has established itself as a trusted provider of choice so let's embark on a journey
discover the best data analyst certifications available for you are you eager to step into the exciting world of
data analytics look no further than simply learn postgraduate program in data analytics this comprehensive
program is designed to equip you with the essential skills and knowledge needed to thrive in this rapidly
evolving field let's look into the extraordinary features and benefits that make this program truly stand out from
the crowd first and foremost simply learns Career Services is here to ensure that your talent are noticed by top
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the program you will receive a prestigious postgraduate program certificate powerful Testament to your
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opportunities to further enhance your learning experience we have introduced an exclusive partnership with industry
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receive Cutting Edge knowledge and stay ahead of the curve at simply learn we believe in in the power of Interactive
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participate in discussions and gain practical insights that will deepen your understanding of the subject matter one
of the defining feature of our program is the Hands-On approach to the learning through our Innovative applied learning
model you will have the remarkable opportunity to work on a variety of real world projects using industry data sets
for reputable sources such as Google Play Store and the World Bank with our 14 data analytics project your best you
will gain valuable practical experience and develop an impressive portfolio that showcases your skills to potential
employers to enrich your learning joury even further we present Master Class delivered by esteemed faculty from
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perspective ensuring that you receive a well rounded in data analytics now you may be wondering if this program is
suitable for you the answer is yes our postgraduate program in data analytics is thoughtfully designed to the need of
all working professional whether you are an experienced data analyst looking to upskill or someone
new to the field this program is perfect fit no prior programming knowledge is required as we cover everything from the
fundamentals to Advanced Technologies throughout the program you will acquire a wide range of skills essential for
Success career in data analytics these includes data analytics statical analytics using Excel data analysis with
python and R data visualization using W and powerbi model on linear and logistic recursion clustering using k mean and
supervised learning Technologies our comprehensive curriculum ensures that you are equipped with the necessary
tools to excel in this rapidly growing field so why wait any longer join simply learns postgraduate program in data
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business analytics using Excel SQ programming Foundation using python data analytics with r programming and Tabo
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the link in the course page in the description box below hi guys this is R from Simply learn and today we're going
to look at three very important data related roles in the field of data science and then we're going to pit them
against each other so welcome to data scientist versus data analyst versus data engineer now let's have a look at
what's in store for you firstly we'll talk about the job description descriptions the skill sets required for
each role the salary the roles and responsibilities and the companies hiring for these positions so now let's
have a look at each of these roles in detail first off let's have a look at data scientist now a data scientist is
able to create machine learning based tools or processes within the company now they use Advanced Data techniques
such as clustering division trees neural networks and so on so that they can derive business conclusions they are the
senior most member in the team which involves a data engineer as well as a data analyst now they need to have
in-depth knowledge of Statistics data handling and machine learning they also take inputs from data Engineers as well
as analyst so that they can formulate actionable insights for the business now data scientist also needs to have the
same skills as a data analyst and an engineer but needs to have a lot more in-depth knowledge and expertise with
these skills next up we have data analyst now a data analyst is someone who's able to translate numeric data
into a form that everyone in the organization can understand now this is an entry-level position in the data
analytics team he or she needs to have technical skills in programming languages such as Python and have
knowledge of tools like Excel and understand the basics of data handling modeling and Reporting now in due time
they can move up the ranks by taking up roles of data engineer and data scientist with some experience that they
can accumulate over the years and finally we have data engineer now data engineer is someone who's involved with
pairing data Who's involved with preparing data for analytical or operation purposes now they are the
intermediary between the data analyst and the data scientist he or she needs to have a lot of experience when it
comes to developing constructing and maintaining architectures now they do generally work on big data and submit
their reports to the data scientist so that they can be analyzed now let's have a look at the skill sets required for
each of these roles first off you have data scientist now since this role is a little more coding oriented you need to
know a great deal when it comes to programming languages programming languages such as python R SQL SAS Java
and so on now you also need to be well ver with Frameworks in relations to Big Data such as Pig spark and doop speaking
of aoop if you want to learn more about how it works I suggest you click on the top right corner and watch our video on
what a do coming back data scientists also need to be welled with machine learning deep learning and other similar
Technologies next up we have data analyst now this role is much less technical as compared to a data
scientist as well as a data engineer considering how its entry level here knowing programming languages is a great
bonus so an idea about programming languages such as python R SQL JavaScript ssas and so on is a great
benefit at the same time you do need to be wellers with tools such as SAS Miner Microsoft Excel ssas SPSS and so on and
finally we have data engineer now being a data engineer requires you to be well wored with a bunch of programming
languages as well as Frameworks now you need to know about programming languages such as python R SQL SAS Java and so on
while having EXP expertise in Frameworks such as Hadoop map reduce Hive Pig Apache spark data streaming nosql and so
on now let's talk about money or the salary each of these roles get firstly we have the data scientist who earns a
is a pretty high salary when you consider that it's only an entry-level job and a data engineer which is in the
median with $116,000 perom now let's talk about roles in the responsibilities firstly we
have the data scientist now a data scientist gets to work with a lot of unstructured data so they need to mine
and clean the data so that it's usable they need to be able to design machine learning models to work on the big data
they need to infer and interpret the analysis on Big Data to be able to lead an entire team to achieve the goals of
the organization and deliver conclusions that have a direct business impact now let's have a look at the roles and
responsibilities of a data analyst they need to use queries to gather information from a database they need to
process the data and provide summary reports they need to use basic algorithms for their work such as linear
regression logistic regression and so on and have core skills in statistics data munging data visualization and
exploratory data analysis and finally we have data engineer now they need to mine through the data so that they can gain
insights from it they need to convert erroneous data into a usable form so that they can be further analyzed they
need to write queries on data they need to maintain the design as well as architecture of the data and create
large data warehouses using ETL or extract transform load now let's have a look at some of the companies hiring for
this role firstly for data scientists you have City Bank Facebook Schneider Intel Amazon and so on for data analysts
you have infosis Oracle Visa Capital 1 Walmart and so on and for data engineer you have Google Cisco flast cognizant
Apple Spotify and much much more now that we have looked at the various steps involved in data analytics let's now see
the different tools that can be used to perform the a steps so as you can see we have seven
tools including a few programming languages that will help you perform analytics better now let's discuss them
Source programming language that supports a range of libraries for data manipulation data visualization and data
modeling python programmers have develop tons of free and open source libraries that you can use you can find many of
software python provides the default package installer called pip or pip Python has libraries such as numpy for
numerical computation of data pandas to manipulate data on numerical tables and time series then you have scipi for
Technical and scientific computations it also provides psychic learn which is a machine learning library for creating
classification regression and clustering algorithms and finally it also has py torch and tensorflow for deep
learning up next we have r r is an open- Source programming language majorly used for numerical and
statistical analysis it provides a range of libraries for data analysis and visualization some of these libraries
are ggplot tidos plotly deer and carrot then we have tblo tblo is a popular data visualization and analytics tools that
helps you create a range of visualizations to interactively present the data build reports and dashboards to
show case insights and Trends it can connect with multiple data sources and give hidden business insights and
intelligence tool developed by Microsoft that has an easy drag and draw functionality and supports multiple data
sources with features that make data visually appealing powerbi supports features that help you ask questions to
Trends so the next tool is Click view click view provides interactive analytics with in memory storage
technology to analyze vast volumes of data and use data discoveries to support decision- making
it provides social media Discovery and interactive guided analytics it can manipulate huge data
data analytics engine to process data in real time and Carry Out complex analytics using SQL queries and machine
writing SQL queries it also has spark MLB which is a library that has a repository of machine
SAS SAS is a statistical analysis software that can help you perform analytics visualize your data write SQL
queries perform statistical analysis and build machine learning models to make future predictions SAS empowers our
customers to move the world forward by transforming data into intelligence SAS is investing a lot to
drive software Innovation for analytics Gartner has positioned SAS as a magic quadrant leader for data science and
analytics data analytics is being used in almost every sector of business these days let's discuss a few of them
when they need it data analytics helps retailers meet those demands retailers not only have an
in-depth understanding of their customers but they can also predict Trends recommend new products and boost
profitability retailers create assortments based on customer preferences invoke the most relevant
engagement strategy for each customer optimize supply chain and Retail operations at every step of the customer
Journey the second application is on Healthcare Healthcare Industries analyze patient data to provide life-saving
diagnosis and treatment options they also deal with healthcare plans and insurance information to drive
key insights using analytics they can discover new drugs and come up with new drug development methods
Imaging at number three we have manufacturing for manufacturers solving problem is nothing new they fight with
difficult problems and situations on a daily basis from complex Supply chains to motion applications to labor
constraints and Equipment breakdowns they deal with such problems on a regular basis using data analytics
manufacturing sectors can discover new cost saving and revenue opportunities the fourth application is
structured and unstructured data to derive analytical insights and make sound financial decisions using
analytics they can find out probable loan defaulters customer turnout rate and detect fraudulent transactions
analytics to develop new business models that can ease their business and improve productivity they can optimize routes to