The Ultimate Guide to a Career in Data Analytics: Roles, Responsibilities, and Skills

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

agenda craving a career upgrade subscribe like and comment below dive into the link in 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

future holds for Professionals in this domain let's take a look at the growth of

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

to identify opportunities for solving business problems data analysts write complex SQL

queries scripts and store procedures to gather and extract information from multiple

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

inferential statistics most importantly you need to have a good workking knowledge of

various data visualization software along with presentation skills this will help you pitch in your ideas and

viewpoints to the clients and stakeholders better now talking about their salaries

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

business analyst business analysts help guide businesses in improving products

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

recommendations and reports to Executives and stakeholders business analysts are

responsible for creating new models that support business decisions and come up with initiatives and strategies to

optimize costs now let us look at the various responsibilities of a business

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

business process models along with knowledge of programming languages ideas about

statistical analysis and predictive modeling is necessary decision making strong

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

Young a few of the companies hiring for business analysts up next we have the job role of

a database administrator a database administrator is a specialized computer systems

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

that database administrator will ensure that the data is secure from unauthorized

access moving on to their responsibilities a database administrator develops designs and

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

utilize systems they need to cooperate with programmers data analysts and the IT

staffs to ensure smooth running and maintenance of databases database administrators are

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

with storage Technologies talking about their salary a database administrator in India can

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

for businesses a data engineer is an intermediary between a data analyst and a data

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

while they can earn around $103,000 a year in the USA we have Cap Gemini Shutterstock the

American provider of stock photography Spotify Accenture genpac and Facebook hiring data

Engineers the next exciting job role is of a data scientist a data scientist is a

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

statistics computer science and information science a data scientist understands the

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

Solutions and opportunities a data scientist takes input from data analysts and Engineers

to formulate the results they use visualization packages and tools to create reports and

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

of a data scientist a bachelor's degree in computer science or information

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

Java and C++ knowledge of pearl will also be an advantage

familiarity with Apache Hive Pig and Apache spark is necessary along with the knowledge of

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

earn up to $113,000 per anom that's a lot of money from the many companies hiring for

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

vast amounts of data and apply knowledge without human intervention they use different

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

responsibilities of a machine learning engineer machine learning Engineers research

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

same domain they should be proficient in programming languages such as python R

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

they can earn around $114,000 a year now that's a whopping amount isn't

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

how an ideal resume of a data analyst should look like seen on your screens is a sample

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

data delivery finally you can speak a bit about your reporting skills and if

needed elaborate on it usually professionals would have worked in a similar domain before

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

extracurricular activities that you are good at so this is how an ideal resume of a

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

the following is not a python library for visualization M lot lip sapai pandas

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

use some of the tools as a data analyst what are that first is Microsoft Excel it is the

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

additional features that help simplify data manipulation as a programming language

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

pre-processing data or building more complex calculations you might have heard about

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

are the skills are and how it is used what are you up to in an organization as a data

analyst to create and evaluate the report using automated tools like table or power

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

commitment and expertise in the field of data analytics this certificate holds a value that can open several career

opportunities to further enhance your learning experience we have introduced an exclusive partnership with industry

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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

whopping $137,000 per anom then we have the data analyst who earns $67,000 per anom which

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

one by one first we have python python is an objectoriented open-

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

them via the python package index which is pypi the repository of python

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

patterns then we have a competitor of Tableau which is powerbi powerbi is a business

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

your data and get immediate insights you can also forecast your data for predicting future

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

sets instantly with accuracy up next we have Apache spark Apachi spark is an open source

data analytics engine to process data in real time and Carry Out complex analytics using SQL queries and machine

learning algorithms it supports spark streaming for realtime analytics and Spark SQL for

writing SQL queries it also has spark MLB which is a library that has a repository of machine

learning algorithms and then it has graphics for graphical computation and finally we have

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

machine learning moving on to the applications of data

analytics data analytics is being used in almost every sector of business these days let's discuss a few of them

first we have retail customers expect retailers to understand exactly what they need and

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

Advanced analytics allows healthcare companies to improve patient outcomes and

experience cancer cells and diabetic retinopathy can be discovered using Medical

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

related to the banking sector Banking and financial institutions collect vast volumes of

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

immediately the final application is based on Logistics logistics companies use data

analytics to develop new business models that can ease their business and improve productivity they can optimize routes to

ensure delivery reaches on time in a cost efficient manner they also focus on improving aut processing capabilities as

well as Performance Management with that now let's look at the companies using data analytics on a

daily basis so we have the e-commerce giant Amazon then we have Accenture followed

by the American Health Care Service organization siga then we have the American supplier

of Health Information Technology Solutions Services devices and Hardware cner followed by Target and Antivirus

Company mac Cafe next we have Rapido which is an Indian bike rental company based in Bangalore

after that we have Flipkart and the world's largest retail company Walmart with that let's understand a

case study from Walmart and how it uses data analytics to grow its business and serve its customers

better Walmart is an American multinational retail company that has over 11,500 stores in 27 countries

worldwide and it has e-commerce websites in 10 different countries it has more than 5,900 retail units operating

outside the United States with 55 banners in 26 countries with more than 7 lakh Associates serving more than 100

million customers every week it has over 2.2 million employees around the world and 1.5 million

employees in the United States alone Walmart's e-commerce Branch alone employs more than 3,000 technologists

from Silicon Valley to India England and South America more than 240 million customers

shop at Walmart each week online and at its Banner stores walmart.com sees up to 100 million unique visitors a month

according to Comm score and is growing every year Walmart collects over 2.5 petabytes

of data from 1 million customers every hour that's really huge now to make sense of all this

information Walmart has created data Cafe a state-of-the-art analytics Hub located within its Banton Val Arkansas

headquarters here over 200 streams of internal and external data including 40 petabytes of recent transactional data

can be modeled manipulated and visualized teams from any part of the business are invited to bring their

problems to the analytics experts and then see a solution appear before their eyes on the nerve centers touchscreen

smartboards Walmart also constantly analyzes over 100 million keywords to know what people near each store are

saying on social media to understand the customer behavior on what they like and dislike Walmart uses modern tools and

Technologies to derive business insights and improve customer satisfaction action some of these tools include python SAS

nosql databases such as cassendra and Hadoop Now using all these Technologies and data analysis techniques Walmart can

better manage its supply chain optimize product assortment personalize the shopping experience give relevant

product recommendations and finally optimize and analyze Transportation lanes and routes for its Fleet of

trucks with that let's jump into our use casee demo where we will predict the sales based on

Advertising expenditure using the linear regression model in R the advertising expenditure has been

made via different mediums such as radio television and newspaper we will use the r programming

software to implement the demo so why R well R is a free and open- Source

software that can be downloaded from the arran website it is easy to learn and use our language is built specifically

for performing statistical analysis data manipulation and data mining using packages such as plier deer tier and

lubridate R supports data visualization with the help of packages such as ggplot Google v r color Brewer leaflet and GG

map and finally the r software can be used in a wide range of analytical modeling including classical statistical

test linear and nonlinear modeling data clustering time series analysis and

more now let's have a look at our data that we will be using for this demo here is our advertising CSV data

set which has four columns you can see this tv ads expenditure the next column is for radio ads then we have the

newspaper ads and the last column colum is our Target column that is the sales so the data set

has in total 200 rows now to understand the data Let me Give an

example so consider the second row so suppose you spend around $230 on TV ads then $ 37.8 on radio ads and $ 69.2 in

newspaper ads ad you can expect to sell nearly 22 units of a particular product

similarly if you are spending $44.5 in TV advertising $ 39.3 in radio ads and $45 in newspaper ads you can sell around

10 units of certain item we will analyze this data using linear regression so linear regression is a supervised

learning algorithm which means the data has labeled columns and is used to predict numeric continuous variables so

our sales column here is the target column and it has continuous numeric variables now let me go to the r studio

and start with the demo so first I'll create a new file then I'll select our

script the next step is to install all the necessary packages that we need for this demo if you already have the

packages installed in your R Studio you need not do it again you can just call these packages using the library

function and pass the package names so first I will install the deer package which is used for data manipulation I'll

be using install. packages function and I'll give the package name so I'll type install dot packages

if you hit tab it will autoc complete then under quotations I'll write

deer I'm not going to run this because I already have it installed in my R Studio The Next Step I'll write I'll

call this uh package using Library function I'll give the package name depler I'll run

this then I'll install the broom package it takes the messy output of buil-in function functions in R such as linear

model or LM then T Test and turns them into a tidy data frame so I'll copy the ABB code I'll

just paste it again I'll change it to broom here also I'll change it to

broom I'll run this okay then I'll be installing the ca

tools package which will help us build our linear regression model I'll paste the same code and I'll

take CA tools and I'll call that using the library

function I'll run this now sometimes people face issues with installing this particular package

if you also face this problem do visit the R Studio Community page now let me show it to