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

Key Takeaways

data has always been Centric to any decision making today's world runs completely on data and none of today's organizations would survive a day without bytes and megabytes there are several roles in the industry today that deals with data and most people have several misconceptions about them I am ayushi from edureka and let me welcome you to this video on the key differences between three of the leading roles in data management that are data analysts data engineer and data scientist so let's move on and see what all we're going to cover in this session first and foremost we'll be starting by getting a quick introduction about the rules as in who is a data analyst data engineer and a data scientist then we'll be going through the various skill sets that these professionals possess we'll also be looking at various roles and responsibilities and finally I'll conclude this session by telling you guys the salary of what a data analyst a data engineer and a data scientist earn so let's begin this session and start with the very first topic who is a data analyst well a data analyst is the one who analyze all all the numeric and other kinds of data and translate it into the English language so that everyone can understand now this data is used by the upper management to make informed business decisions now the main responsibilities of a data analyst include data collection collation analysis and Reporting next is data engineer so a data engineer is the one who is involved in preparing data for analytical or operational uses so these are the ones who develops constructs test and maintain the complete architecture of the large scale processing system now a typical data Engineers day include building data pipelines to pull all the informations together from different sources they then integrated Consolidated for the clean and structure it for more analytics so this probably varies from organization to organization next is your data scientist so a data scientist is a one who analyze and interpret complex Digital Data for instance statistics of a website now a data scientist is a professional who deals with your large amount of structure as well as unstructured data they use their skills in statistics programming machine learning in order to create strategic plans now data scientist and data engineer job roles are quite similar but a data scientist is the one who has the upper hand on all the data rated activities when it comes to business related decision making data scientists have the higher proficiency now let's look at the roadmap which correlate these three job rules to start off with most entry-level professionals interested in getting into Data related jobs start off as data analyst so qualifying for this role is as simple as it gets all you need is a bachelor's degree and good statistical knowledge well strong technical skills would be a plus and can give you an edge over most other applicants other than this companies expect you to understand data handling modeling and Reporting techniques along with a strong understanding of the business moving forward the transition between a data analyst role and a data engineer one is possible in multiple ways you can either acquire a master's degree in a data edit field or gather amount of experience as a data analyst adding on to the skills of data analyst a data engineer needs to have a strong technical background with the ability to create and integrate API also need to understand data pipelining and performance optimization the next milestone in data ingenious career is becoming a data scientist well there are several ways in which a data engineer can transition into a data scientist role the most seamless one is by acquiring enough experience and learning the necessary skills now these skills include Advanced statistical analysis a complete understanding of machine learning and predictive algorithms and data conditioning next let us compare these different roles on the basis of their skills their roles and responsibilities in their day-to-day life and finally discuss the salary perspective first let us see what are the different skill sets required for data analyst data engineer and data scientists so as discussed a data analyst primary skill sets revolves around data equation handling and processing now an ideal skill set for this profile would include data warehousing Adobe and Google analytics then you must have programming knowledge scripting and statistical skills reporting and data visualization using various tools database knowledge like SQL or anything and spreadsheet knowledge well a beginner's level programming experience would also Aid in building better statistical models as well now a data engineer on the other hand requires intermediate level understanding of programming to build thorough algorithms along with a Mastery of statistics and math most companies hiring for data Engineers look for skills like data warehousing and ETL or you can say extract transform load then it has some Advanced programming knowledge also hadoop-based analytics play a vital role then they must have in-depth knowledge of databases data architecture and various machine learning concept or you can say algorithms knowledge finally a data scientist needs to be master of both the worlds data stats and math along with in-depth programming knowledge of machine learning and deep learning well the job description for an ideal data scientist statistical and analytical skills then you have various data mining activities machine learning and deep learning principles or you can also add up to its various algorithms that a data scientist should also have in that programming knowledge or you can say such as in SAS r or python languages now that you have a complete understanding of what skill sets you need to become a data analyst a data engineer or data scientist let's look at what are the typical roles and responsibilities of these professionals now the roles and responsibilities of a data analyst data engineer and a data scientists are quite similar as you can see from the slides now a typical data analyst is responsible for statistical analysis and data interpretation this should also be well familiarized with various data reporting and visualization tools for example if you're working on python you should know the various python libraries like matplotlab C born Etc and similarly if you are familiar with our language then you should go for ggplot or any other visualization library then a data analyst should never compromise on the quality this should also be very friendly with data rated works for example data equation maintenance pattern detection data cleaning and things like that next comes your data engineer well adding on to the work of data analyst a data engineer also maintains the architecture the development of it and the testing of that architecture so it basically involves developing data sets using machine learning techniques or you can say a data engineer should also know how to deploy these machine learning and deep learning models and all the other tasks assigned with them so for example predictive modeling searching for hidden patterns and similar tasks then comes your data scientist now a data scientist on the other hand is responsible for a lot of tasks it is responsible for mining of data then develop operational models then a data scientist should also be exported machine learning and deep learning techniques she should also be scaled in data enhancement and sourcing methodologies another important aspect of being a data scientist is strategic planning and data integration now a lesser known task of a data scientist is impulsive or you can say or ad hoc analysis and finally a data scientist must be scaled at anomaly detection and performance tracking now after these two interesting topics let's now look at how much you can earn by getting into a career in data analytics data engineering or data science now as you can see the typical salary of a data analyst list is just under 59 000 per year whereas a data engineer can earn up to ninety thousand eight hundred and thirty nine dollars per year whereas a data scientist can earn up to ninety one thousand four hundred and seventy dollars per year so isn't this amazing guys now looking at these figures of a data engineer and a data scientist you might not see much difference at first but delving deeper into the numbers a data scientist can earn 20 to 30 percent more than an average data engineer also it's been proven by various job posting from companies like Facebook IBM that basically code salaries up to one thirty six thousand dollars per year now taking this into consideration we also have an expert curated data science Masters program wherein you can find all the necessary details to become a data scientist it includes 12 courses with 250 Plus hours of Interactive Learning along with a Capstone project you can find out all the details curriculum batch timings everything over here and let me also tell you one more thing guys you will also be awarded with an industry recognized certificate in the end so do check out this page guys I'll drop the link in the description box below well that's all for today I hope you guys like this session have a lovely weekend enjoy bye bye thank you