Data analyst versus data engineer versus data scientist which one to choose this is one of the most popular questions asked by learners looking for a career in data and analytics i'm sure youtube would have come across these job roles in the ever-growing data science landscape though they all deal with data these .
Jobs are not the same there are significant differences between what a data analyst data engineer and a data scientist does we will look at these job roles and the differences in detail first let's look at some data analytics and data science trends .
The analytics and data science smart data is thriving data analytics data engineering and data science are the key trends in today's accelerating market as per statista.com global big data analytics market revenue will grow at a cagr of 30 percent with revenue reaching over 68 billion us .
Dollars by 2025. according to technavio the enterprise data management market is expected to increase by 64.08 billion us dollars by 2025. as per marketsandmarkets.com the big data market size is projected to grow from 162.6 billion us dollars in 2021 .
To 273.4 billion u.s dollars in 2026. now another report from research drive says that the data science platform market is estimated to reach 224.3 billion us dollars by 2026. so with so much data available and companies making huge investments to drive business and sites the job .
Opportunities for data analysts data engineers and data scientists are going to increase in 2022 and over the coming years now let's learn the major differences between data analyst versus data engineer versus data scientist so .
Who are they a data analyst analyzes and interprets vast volumes of data in order to extract meaningful information out of it they find solutions to a business problem and make critical business decisions the insights provided by data analysts are important to companies that want to .
Understand the needs of their end customers now talking about who a data engineer is a data engineer on the other hand builds infrastructure and scalable pipelines to manage the flow of data and prepare it for analysis so basically they optimize the systems .
That enable data analysts and data scientists to perform their job efficiently data scientists are professionals who analyze and visualize existing data and use algorithms to build predictive models for making future decisions they also engage with business leaders to understand their needs and present .
Complex findings with that let's look at the primary roles and responsibilities of these three job roles data analysts are responsible to collect clean store and process data they discover hidden patterns from data by performing exploratory data analysis and visualize data by creating charts .
And graphs acquiring data from primary and secondary sources is one of their key tasks the build reports and dashboards and also maintain databases now talking about the roles and responsibilities of a data engineer a data engineer performs data .
Acquisition the design build and test data as well to develop and maintain data architecture data engineers are tasked with testing integrating managing and optimizing data from a variety of sources so they integrate data into existing data pipelines prepare data for modeling and .
Perform various etl operations now talking about the roles and responsibilities of a data scientist so data scientists develop machine learning models to identify trends in data for making decisions that develop hypothesis and use the knowledge of statistics data visualization and machine learning to .
Forecast the future for the business data scientists visualize data and use storytelling techniques and also write programs to automate data collection and processing now move on to the skills possessed by data analysts data engineers and data scientists to become a data analyst you need to .
Have good hands-on experience with writing sql queries you should have excellent microsoft excel skills for analyzing data data analysts are also good at programming and they need to know how to visualize data solve business problems and possess domain knowledge .
Data engineers should have a solid understanding of sql mongodb and programming they need to have a good command of data architecture scripting data warehousing and etl data engineers are also good at hadoop based analytics now talking about the skills for a data .
Scientist so a data scientist should have experience with programming in python and r this would have a very good understanding of mathematics and statistics as well data scientists need to possess analytical thinking and data visualization skills as well .
Machine learning deep learning and decision making are other critical skills every data scientist should have now we look at the salaries of a data scientist a data analyst as well as a data engineer so a data analyst in the united states earns over seventy thousand dollars per annum while in india a data analyst can .
Earn nearly seven lakh twenty five thousand rupees per annum a data engineer in the united states can earn over hundred and twelve thousand five hundred dollars per year and in india you can earn over nine lakh rupees per annum we're talking about the salary of a data scientist a data scientist in the united .
States earns over 117 thousand dollars per annum and in india a data scientist can earn over 11 lakh rupees per annum coming to the final section of this video we look at the top companies hiring for data analysts data engineers and data scientists so we have the first company as google then we have .
Tesla next we have the e-commerce giant amazon the internet giant facebook or the social media giant facebook we have the tech giant oracle we also have verizon and airbnb so these are some of the top companies that hire for the three roles and that brings us to the end of this .
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