Friday, May 20, 2022

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

Data has always been Centric to any decision making. Today'sworld runs completely on data and none of today's organizations would survive aday without bytes and megabytes. There are several rolesin the industry today that deals with data and most people have severalmisconceptions about them. I am Aayushi from Edureka and letme welcome you to this video .

On the key differences between three of the leadingroles in data management, that are data analyst, dataengineer and data scientist. So let's move on and see what all we going to coverin this session first and foremost will be startingby getting a quick introduction about the roles as in who isa data analyst, data engineer and a data scientist, then we'll be goingthrough the various skill sets .

That these professionalspossess will also be looking at various rolesand responsibilities. And finally, I'll conclude the sessionby telling you guys this is Leo what a data analysta data engineer and a data scientist learn so let's begin the session andstart with the very first topic who is a data analyst. Well a data analyst is the one .

Who analyzed all the numericand other kinds of data and translate itinto the English language so that everyone can understandnow this data is used by the upper management to makeinformed business decisions. Now the main responsibilities of a data analyst include datacollection correlation analysis and Reporting nextis data engineer. So a data engineer is the one who is involvedin preparing data .

For analytics caloroperational users. So these are the ones who develops constructs testand maintain the complete architecture of the largescale processing system. Now a typical data ingenious, they include buildingdata pipelines to put all the information togetherfrom different sources. They then integratedConsolidated for the clean and structure itfor more analytic 6. .

So this probably varies fromorganization to organization. Next is a data scientist. A data scientist is a one who analyze and interpretcomplex Digital Data for instance statisticsof a website. Now a data scientistis a professional who deals with your large amount of structured as wellas unstructured data. They use their skills .

In statistics programmingmachine learning in order to create strategic plansnow data scientist and data engineer job rolesare quite similar but a data scientist is the one who has the upper hand or allthe data editor activities when it comesto business related decision-making data scientisthave the higher proficiency. Now, let's look at the road map which correlate these threejob roles to start off .

With most entry levelprofessionals interested in getting into Data relatedjobs start off as data analyst. So qualifying for this roleis as simple as it gets. All you need isa bachelor's degree and good statistical knowledge. Well strong technicalskills would be a plus and can give you an edgeover most other applicants other than this companies expect you to understand data handlingmodeling and Reporting. .

Along with the strongunderstanding of the business moving forward the transitionbetween a data analyst role and a data engineer one ispossible in multiple ways. You can either acquirea master's degree in a related fieldor gather amount of experience as a data analyst addingonto the skills of data analyst a data engineer needs to havea strong technical background with the ability to createan integrated API also need to understand data pipeliningand performance optimization. .

The next milestone in data Engineers Courieris becoming a data scientist while there are several ways in whicha data engineer can transition into a data scientist rulethe most seamless one is by acquiring enough experience and learning thenecessary skills. Now these skills includeAdvanced statistical analysis a complete understandingof machine learning .

And predictive algorithmsand data conditioning next. Let us compare these differentroles on the basis of their skills their roles and responsibilitiesin their day-to-day life and finally discussthe salary perspective first. Let us see what arethe different skill sets required for data. Less data engineerand data scientists. So as discussed a data analystprimary skill sets revolves .

Around data equation handling and processing nowan ideal skill set for this profile would include data warehousing Adobeand Google analytics. Then you must haveprogramming knowledge scripting and statistical skills reporting and data visualization usingvarious tools database knowledge like SQL or anythingand spreadsheet knowledge. Well a beginner's .

Level programming experiencewould also Aid in building betterstatistical models as well. Now a data engineer on the other hand requiresintermediate level understanding of programming to build our algorithms alongwith a Mastery of statistics and math most companies hiringfor data Engineers. Look for skills, like data warehousing and ETLor you can say extract .

Transform load then it has someAdvanced programming knowledge. Also Hadoop based analyticsplays a vital role then they must have in-depth knowledgeof databases data architecture and various machine learningconcept or you can say algorithms knowledge fine. Any a data scientistneeds to be master of both the world's data starts and math along with in-depthprogramming knowledge of machine learningand deep learning. .

Well the job descriptionfor an ideal data scientist include statisticaland analytical skills. Then you have various data miningactivities machine learning and deep learning principles, or you can also add upto its various algorithms. Then a data scientistshould also have in-depth programming knowledge or youcan see such as in SAS are or python languages now .

That you havea complete understanding of what skill sets. You need to becomea data analyst a data engineer or a scientist. Let's look at whatare the typical roles and responsibilities of theseprofessionals now the roles and responsibilitiesof a data analyst data engineer and the data scientistsare quite similar as you can see .

From the slides now a typicaldata analyst is responsible for statistical analysisand data interpretation. They should alsobe well familiarized with various data reportingand visualization tools. For example, if Iworking on python, you should knowthe various python libraries like matplotlib see zbornak. Job, and similarly. If you are familiarwith our language, .

Then you should go for ggplot orany other visualization library. Then a data analyst shouldnever compromise on the quality. This should also bevery friendly with data. It works for example data equation maintenancepattern detection data cleaning and things like that. Next comes to data engineerwell adding onto the work of data analyst a data engineeralso maintains the architecture the development of it .

And testing ofthat architecture. So it basically involves developing data sets usingmachine learning techniques, or you can say a data engineershould also know how to deploythese machine learning and deep learning models and all the other tasksassigned with them. So for example,predictive modeling searching for hidden patternsand similar tasks, .

Then comes your data scientist. Now a data scientist on the other handis responsible for a lot of tasks is responsible for mining of data thendevelop operational models. Then a data scientistshould also be explored in machine learningand deep learning techniques. You should also be scalein data enhancement and sourcing methodThese another important aspect .

Of being a data scientiststrategy planning and data integration. Now a lesser-known taskof a data scientist is impulsive or you can sayor ad hoc analysis and finally a data scientistmust be skilled at anomaly detection and performance tracking now after these twointerested topics. Let's now look at .

How much you can earnby getting into a career in data analytics dataengineering or data science. Now as you can seethe typical salary of a data analyst is just under fifty nine thousanddollars per year there as a data engineer can earn up to ninety thousand eighthundred and thirty nine dollars per year. Whereas a data scientistcan earn up to ninety .

One thousand four hundredseventy dollars per year. So isn't this amazing guys nowlooking at these figures of a data engineerand a data scientist, you might not seemuch difference at first but delving deeper into the numbersa data scientist can earn twenty to thirty percent morethan an average data engineer. Also, it's been provenby various job posting from companies .

Like Facebook IBM That basically coat salaries up toone thirty six thousand dollars per year now takingthis into consideration. We also have an expert createddata science master's program where you can find all the necessary detailsto become a radar scientist. It include 12 courseswere 250 Plus hours of Interactive Learningalong with the Capstone project. You can find out allthe details curriculum .

That timings everything over here and let me also tellyou one more thing guys. You will also be awarded with an industry-recognizedcertificate in the end. So do check out this page guys. I will drop the linkin the description box below. Well, that's all for today. I hope you guys like this session havea lovely weekend. .

Enjoy. Bye. Thank you. I hope you have enjoyedlistening to this video. Please be kind enough to like it and you can comment anyof your doubts and queries and we will reply them at the earliest do look outfor more videos in our playlist And subscribe to Edureka channel to learn more. .

Happy learning.

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