Data Engineer, Data Analyst & Data Scientist – Explained by an expert in simple language



kappa yes key tre curly hair coaching Institute's code hi loctifas nape a cannot chat a other ha though buys we are pants or okay make her bad k steady AQ cape and of course Cassatt of IES GRE kar sakthe hain hodge he visit craze steady iq.com so far i have covered in my previous topic about the data science artificially intelligent analytics big data and all today i try to cover something which is not specific to the technology implementation but yes it is more or less the role or a industry which required a people into that particular role though recover topic is again very close to the data science but this is more about the roles and responsibilities people are playing and what type of a studies or what type of a skills person should have to implement that role which we have covered in previous slides as well so the topic is data engineer did analysts and data scientist so today we will talk about what is data engineer in the company what is data analytics in the company and what is data scientist and what type of a knowledge or education skills they required it do this particular side is not very important to understand this rule but it is somewhat need to set a background in the context so when we go to the different roles we need to understand okay what type of activities they are playing and what is the actual activities is there into the data science thing so if you see this particular graph which has given the maturity model of the data science saying that we have actually started from the descriptive analytics which says that yes we have a data and we have captured the data and why this particular thing has been happen so what happened in the past and that we can read it by the data which we have stored in our database and the second is diagnostic analytics so it says ok what happened is what but why did it happen maybe let's say take an example there is in a market crash market is crash because the political reasons because any external reasons because of the flood because of the good movement into the market because of the bad movement into the market so it is actually take it's telling us did why did it happen why market go from up to down because these are the factors which impacted the market to get down and third is predictive analytics predictive analytics means okay whatever happened has happened but with this particular data and whatever the inputs we have what we can predict okay next year what will be happen in the next two months what will be happen whether after this election the rate would be high or do it down if somebody is making that particular party is making a good progress as in a market up or a down I mean I'm not just taking a political example let's say rainy season so if the rainy season is good weather the agriculture cost would be less on a low if the productivity of the agriculture is high whether it will be taking a market on the upper side the lower side whether the export and import is up then the Agriculture's predicts prices going up or going down so these are the predictive analysis we can do into the data sense and then final maturity model is prescriptive analysis so we know that is that would be happen if we are not doing any action but can we do some action so that particular factor or a goal which we have think of for our organizations can be achieved so that particular input is coming as a prescriptive analytics yes so we have more or less three different role into the data science that is what I can categorize it they can be a mold plus and minus so first is the data engineers so if you go in any organizations which is running to data sciences things so they are one person who can not one person a one role which is the data engineers so data engineers is Excel also known as the database administrators and the data arkad what it means so more or less infrastructures more or less whatever these software's more or less whatever the machines monitoring data ETL operations when I say ETL extract the data transform the data and load the data so these particular activity is taken care by the data engineer next one is data analytics so name itself is saying that this particular person is more about analytics T things or maybe making some sort of formula to say okay this is my previous data what happened in the past what will be happen in future let's see what we talked about into the previous slide so it is actually doing some sort of a mathematical or a statistical analysis on the data what data we have so this is the role of the data analytics is saying also known as a business analyst because it is more focused to or aligned to the business goals this is the businesses doing this waz business has done and this will business will do is the role of more about data analytics and the third role as the data scientist so this is also known about the data managers or statisticians so this is a one label above the data analytics data analytics is generally giving a analytics on the previous data and whatever the between happened but when we have to be go about what additional things which we need to see can there be a additional external factor which we do not have considered and if we have considered that what would be the result how it is going to be changed some sort of a machine learning and artificial intelligence is also a part of more or less data scientist because what algorithms need to be implement in the data needs to be take care by editors I mean all what category in which our base this fall from the data perspective data scientist needs to be take if this particular data is in this form this is the best way to go forward or this is the best way to coming up with the business stakeholders decisions as more about our data scientist role so basically we have a three data Engineers data analytics and data scientist data engineers are more about as we call about software hardware applications data expect data analytics is that whatever the data is how we can do a more good analysis on that giving a good results whatever has been happen into the system so far and what can be happened and data scientist is more about focusing to the going trend where we need to take it to the business what is the additional factors which can come up if they come up what would be the impact if we do some changes how it can be changed the impact what is the best algorithm or statistical logic we need to be implement what type of a data we have what is the category of data in which we fall is the role of the data scientist so now this particular thing is saying that what is the basic quality of the data engineers and what is the skills they require in so if I read it for you so there are a generalizations computer science to help the large data sets they typically focus on coding cleaning up the data sets and implementing the requests coming from the data scientist so whatever the data scientist is saying okay data is in this form an ingenious is making the ETL according to that or if they saying that I would be using this particular algorithm engineers coming up that which language or which coding I need to do to implement the idea which has been giving by the data centers so skill is programming mathematician and the Big Data so he would be good in mathematics he would have an idea about the Big Data software like an Hadoop's ecosystems and all and he would be a good programmer as well to implement that whatever the inputs are logics or a brain points coming from the data scientist so they know how do they know no sequence pythons if they are moral to the open world open source well but there are other ecosystems from the soft or AWS or all these your sights as well now coming to the data analyst so they are typically help people from across the company understand specific theories with charts so they are the people who are bridge between the business and the technologies so they read out the requirement they make the chart according to them when I see recharge the data what the business stakeholder is needed to take the decisions they are coming up with data think of the Kure that what carry I need to be give on to the big data or a data so they can be giving us those particular responses into the report form or a chart form is the data analyst so their skills are statistics communications and the business knowledge so they they should know domain knowledge they have a good communicator then only you can go and talk to the business people and because they know the domain knowledge as well they can talk into the business domain terms and that is how it has been beneficial so some of the programming such as Excel W sequel is is good for them so if they know Excel is really really important sequel is also important because they have to be going to the Curie's tableau or the other dashboard because they have to make a chart or a dashboard so the business people can see and finally visualize it at how it is coming up data scientist so data scientist will be able to take a data science project from end to end so this is the the actually a program manager sort of person they can help store images amount of data create predictive modeling process and present the findings so that is what the first slide was important it what is the predictor what is Prescriptives timely because n 2 and V if we have to be go that is a data scientist a person who drive all the chain so they come up with the idea and the plan and then the data engineers and data analysis help them to achieve in all the phases what type of a skills data scientist is required as mathematical programming and communication and what type of a programs they would be needing is sequel Python or R so the person will not avail that what is R or a Python it's more about mathematical library which gives these statistical formulas an algorithm to run the queries and get the data so this is how data scientist data in engineers and data analytics is basically at three different roles into the data sciences nowadays and it is important to understand when when one need to be go to the data science field in which area he wants to be pursue and it is noting that first we have to go for a data engineers then we need to go for a data scientist and then the data analyst it can be anything you can directly dump to jump to the data scientist you may not need an exposure of all these tools and technologies but yes awareness of that particular point is important but the data scientist rule is more about planning giving a thoughts and coming with the insights and data analytics is more good into the communication and domain so they can give each arts and the the excel sheets and data for that and data engineers are more about making the things happen whatever the data scientists and data analysis are thinking of I hope I am able to give you the clear pictures of these three different roles which can help you out whenever you go for any data sciences training or whenever go to any university we are producing the all data sciences course and where you want to be pursue your career going forward thank you

19 Comments

  1. Study IQ education said:

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    June 27, 2019
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  2. Deepika Sharma said:

    Explained well

    June 27, 2019
    Reply
  3. Oliver Joshua Jacob said:

    Thanks for such an in-depth explanation. Could you please make a video explaining the different skills required to get into cloud computing?

    June 27, 2019
    Reply
  4. BN S said:

    Hi, can you add English subtitles please, alternatively, could you create the same video but in English

    June 27, 2019
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  5. Vaishnav Srivastava said:

    Sir can i ask u 1 question plzzz????

    June 27, 2019
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  6. Shobhit Agarwal said:

    Good video, good explanation

    June 27, 2019
    Reply
  7. Energy economics & Data science said:

    Wow! now Study iq enter in this field

    June 27, 2019
    Reply
  8. Udit Kumar Pradhan said:

    I don't know why the bad comment are come.. Bdw Nice session sir… Please tell more about R language

    June 27, 2019
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  9. Manas G said:

    Nice Sir. Really helpful

    June 27, 2019
    Reply
  10. Sandeep harishchandra Patil said:

    Sir Same lecture please given in hindi

    June 27, 2019
    Reply
  11. rupali taneja said:

    thank you so much for telling. it is really helpful.

    June 27, 2019
    Reply
  12. राष्ट्रवादी भारतीय said:

    Nice explanation.thanks

    June 27, 2019
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  13. shubham maurya said:

    hindi me sir ji

    June 27, 2019
    Reply
  14. dhanush n said:

    This video doesn't fit into your channel

    June 27, 2019
    Reply
  15. 1million Gaana said:

    very good Sir thoda speed tej kijiye aur bath K padhaiye

    June 27, 2019
    Reply
  16. eekendra oom said:

    Faltu hai.

    June 27, 2019
    Reply
  17. yash u said:

    Sir I am currently doing bsc statistics so should I go for MCA or msc it or msc computational statistics and informatics to become data scientist?
    Please sir reply

    June 27, 2019
    Reply
  18. Aakash Sharma said:

    Sir.. these idea is very helpful ..can upload same video in hindi language also…

    June 27, 2019
    Reply
  19. Study Plus said:

    Pehle laga sharmaji agaye from sharma ji technical channel

    June 27, 2019
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