Very understandable approach to explaining the differences in these roles. It's definitely appreciated, especially with the blurred lines that companies often use to represent these fields.
Most of these companies don't even know the difference between Computer Science, Software Engineering and Information technology . They think it's a same thing.
I work as a Data Analyst / Engineer / Scientist as is the case with most people working in smaller companies. I don't excel at any of the three areas except maybe engineering because I'm the only one who does it on my team, not because I'm actually good at it. For every insight I find, someone else can find 5 more, for every model I build, someone else will always build a model with better performance. It drives me crazy but it is what it is I suppose. Another thing about working in smaller companies is that solutions are usually frowned upon because of the extra costs. It's annoying to have to write everything from scratch from pipelines to dashboards, but it's also a good learning experience.
is a bachelors in business data analytics worth it ( the program has machine learning business finance and a programming course aswell )or is something general like Econ or Computers better ? I wanna do a masters afterwards most probably in Computer science or IT
@@aena5995 Sounds like a good choice. I don't recommend going into pure Data Science courses simply because of how vast the field is. Having a narrower focus helps you carve out your own niche, and if business / finance is the area of Data Science you're personally interested in, go for it
Same here. Though I did work for a company that had a separate team of SQL programmers for preparing our data & another team that performed QA. By the time I got the data it was ready to plug into R or SAS.
Hello, Mr. Daniel! I am 17 years old boy with no tech background and bad math who wants to work as a data scientist in the near future. If it is no problem, could you give me some advices how I can start?
Thank you so much for giving us not only the differences, but also how the market uses the terms. You made everything very clear for me now. Congrats on the video!
This video was incredibly helpful in clarifying job titles within the job market, and I no longer feel as though I'm struggling. Great explanation! Thanks !!
Thanks for sharing such a valuable information on Google Software Engineers and their multifaceted roles as Data Scientist, Research Scientist, ML Engineers, Data Analyst. Brilliant explanation.
No real life difference, bro. Managers barely understand the difference between a programmer and a bartender, so they'll throw you into whatever tech role as long as you can turn a pc on.
Perfect Video explanation // having worked several Oracle Federal Projects as a Software Engineer ....i am moving on to the Next BIG Thing : "DATA Scientist" ...seems its all about Forecasting & Predictive Analytics //
Really nice video. I am a current data analyst at a large tech company, hoping to become a ML engineer eventually (similar to a google software engineer whose capable of everything in that chart). Love the content, keep it up.
No. If you want to become a data scientist, let others do the data cleansing and IT diagnosis things. I was a victim of this - ex company paid me only one person's salary, while I did MLOps job + i18n + PPT making. It's not worth it unless they pay you enough.
@@hanchengyu3119 not only that but "capable of everything" is not a good thing. Someone who is specialized will always perform better. Much better to make well functioning teams than thin out the skills of everyone and get sub par results for everything.
@@thefourthbrotherkaramazov245 is a bachelors in business data analytics worth it ( the program has machine learning business finance and a programming course aswell )or is something general like Econ or Computers better ? I wanna do a masters afterwards most probably in Computer science or IT
I am a marketing project manager and i was wondering if i could shift my path to data scientist/analyst, and your amazing video made it clear for me, thanks very much
Data Science/Machine Learning/Data Engineering/Data Analyst roles are incredibly overhyped and actually are not very rewarding. The competition is insane and getting a job takes almost 18 months of grinding to break into the industry. Plus you need a masters in Data Science to actually be considered for most roles. But even despite that, you are not considered for most jobs if you don't have work experience. To add on top of that, there are insanely long hours and crazy work pressure, but relatively low pay in these fields,, You must choose your field smartly for the future - Java and Cybersecurity roles along with, network engineer, VLSI, and networking roles are always hiring. So are, product management, Salesforce, and PPM type of roles. Core fields are great but they just aren't that much in demand. Always choose IT or CS or Electrical/Networking and learn to code in Java or Javascript. You are pretty much guaranteed to get a high-paying job.
@@mohit4902i was thinking of going to the data science route since my field is research but seeing your ans make me doubtful 😅😅 either way i love computers.
Companies nowadays prefer a generalist over a specialist who is super expert at one specific field only. This is why developers experience burn outs so often, they have almost no option but to spend a great portion of their time trying out new tech, and whatever they learn will most likely be replaced by "better" resources.
Most data professionals burn out even before they reach 30. But the sad part is they don't even get paid as well as quants or other similar mathematical professions do
As a software engineer I've been doing all this for 20 years, before the "analyst" position became normalize. My job title on one job was Programmer Data Analyst
subs.. I've been seeing your video on my feed for a while now since I started roaming around to study software development but my true goal was to go up to the data scientist role, that's just the goal I have in mind and you just revealed to me that I don't exactly NEED to become a software engineer first if I can land myself to a data analyst role, the hierarchy showed me I can still walk up slowly to reaching my goal.. you are a god send.. :)
Data Science/Machine Learning/Data Engineering/Data Analyst roles are incredibly overhyped and actually are not very rewarding. The competition is insane and getting a job takes almost 18 months of grinding to break into the industry. Plus you need a masters in Data Science to actually be considered for most roles. But even despite that, you are not considered for most jobs if you don't have work experience. To add on top of that, there are insanely long hours and crazy work pressure, but relatively low pay in these fields,, You must choose your field smartly for the future - Java and Cybersecurity roles along with, network engineer, VLSI, and networking roles are always hiring. So are, product management, Salesforce, and PPM type of roles. Core fields are great but they just aren't that much in demand. Always choose IT or CS or Electrical/Networking and learn to code in Java or Javascript. You are pretty much guaranteed to get a high-paying job.
Where does the role of Chatgpt fit in this chart? I read that entry level data analyst tasks can now be done in seconds by Chatgpt. Please elaborate on this.
25h per day could be possible if the person was traveling, some places in the word change hours when the day light is shorter or just by changing setting in the phone can eventually lead to 25h per day. But i get it, it better get rid of weird datas so it is easier to predict later
What I learned working at multiple companies is this, MOST COMPANIES DONT KNOW JACK SHIZNIT ABOUT DATA. Aside from finance & insurance companies, most places don’t have the discipline or stomach for investing in a true data first company. And that especially includes SW companies.
Very understandable approach to explaining the differences in these roles. It's definitely appreciated, especially with the blurred lines that companies often use to represent these fields.
Most of these companies don't even know the difference between Computer Science, Software Engineering and Information technology . They think it's a same thing.
Mm.. but it kind of is. And tbh I think that there shouldn't really be a distinction made across the three, each should know a bit of the others.
didn't expect joma to be this informative
I wanna laugh😂
Incroyable.
@@fatimaWr2 hahahaha
🤣
Good to know he can do It too. I was waiting the part to laugh, but surprise about how really usefull this information was for me.
great video! thanks for clearing that up and explaining the various elements of so many different roles in this field! very helpful.
25 hours a day are possible on days where you return from daylight saving time to standard time.
Uh-huh
Or if an individual moves from one timezone to another.
Or if you're a daywalker
Or just write a flipping program for a virtual 25 hours day.
Jeeezzzz
Possible But highly Unlikely.
I work as a Data Analyst / Engineer / Scientist as is the case with most people working in smaller companies. I don't excel at any of the three areas except maybe engineering because I'm the only one who does it on my team, not because I'm actually good at it. For every insight I find, someone else can find 5 more, for every model I build, someone else will always build a model with better performance. It drives me crazy but it is what it is I suppose.
Another thing about working in smaller companies is that solutions are usually frowned upon because of the extra costs. It's annoying to have to write everything from scratch from pipelines to dashboards, but it's also a good learning experience.
is a bachelors in business data analytics worth it ( the program has machine learning business finance and a programming course aswell )or is something general like Econ or Computers better ? I wanna do a masters afterwards most probably in Computer science or IT
@@aena5995 Sounds like a good choice. I don't recommend going into pure Data Science courses simply because of how vast the field is. Having a narrower focus helps you carve out your own niche, and if business / finance is the area of Data Science you're personally interested in, go for it
Same here. Though I did work for a company that had a separate team of SQL programmers for preparing our data & another team that performed QA. By the time I got the data it was ready to plug into R or SAS.
thanks for sharing your experience. thats why i love the comments to a topic i m interested
Hello, Mr. Daniel! I am 17 years old boy with no tech background and bad math who wants to work as a data scientist in the near future. If it is no problem, could you give me some advices how I can start?
Thank you so much for giving us not only the differences, but also how the market uses the terms. You made everything very clear for me now. Congrats on the video!
This video was incredibly helpful in clarifying job titles within the job market, and I no longer feel as though I'm struggling. Great explanation! Thanks !!
Jesus is your answer to every struggle!! Amen.
@@isaaclovesJesus bruh
That's a very nice explanation, I'd love to see each step in-depth
Thank you! It's so clear now! You're awesome!
Thanks! Cleared the difference really well!
I like your formal videos much more than fun ones. Thank you.
Awesome video exactly what I needed! Thank you!
Thanks a lot, I'm working as Data Analyst and this content made it clear for me!
Your videos are a HUGE inspiration!! just started out my own youtube (from my experience as a data analyst) All the best!
Thanks for sharing such a valuable information on Google Software Engineers and their multifaceted roles as Data Scientist, Research Scientist, ML Engineers, Data Analyst. Brilliant explanation.
No real life difference, bro. Managers barely understand the difference between a programmer and a bartender, so they'll throw you into whatever tech role as long as you can turn a pc on.
Simple , clear , thanks man
Excellent video! I have been looking for this explanation. This also helps me to know where to start learning in terms of data science. Thanks!
Excellent video! The best video on this comparison
I've watched
very valuable that it helps me to identify what project and skills in what order I have to learn first.
Yep, I can confirm as a PhD research scientist that I do in fact have a side kick ML engineer (actually 3) to help me create all my crazy shit.
Perfect Video explanation // having worked several Oracle Federal Projects as a Software Engineer ....i am moving on to the Next BIG Thing : "DATA Scientist" ...seems its all about Forecasting & Predictive Analytics //
I have seen many videos for the last few months within this topic, but THIS video is the most comprehensive for now.
Great video, now I can finally understand and compare different job listings more effectively
Thank you for your advise dataiku
Thank you!! This video helped me a lot about this subject.
This is a really great video to clarify the various data needs companies usually have, and where each role comes in! Thanks a ton!
Thanks for giving all this information.
So well explained .. thank you!
Brilliant explanation! THanks
I know zero about tech yet I understood everything you explained. Bravo
Thank you very much for this video!
This was such a helpful video man you are the GOAT
Great video. Thank you!
what a great explanation! thank a lot
Really nice video. I am a current data analyst at a large tech company, hoping to become a ML engineer eventually (similar to a google software engineer whose capable of everything in that chart). Love the content, keep it up.
Is the salary good ?
Is the salary good ?
No. If you want to become a data scientist, let others do the data cleansing and IT diagnosis things. I was a victim of this - ex company paid me only one person's salary, while I did MLOps job + i18n + PPT making. It's not worth it unless they pay you enough.
@@hanchengyu3119 not only that but "capable of everything" is not a good thing. Someone who is specialized will always perform better. Much better to make well functioning teams than thin out the skills of everyone and get sub par results for everything.
@@thefourthbrotherkaramazov245
is a bachelors in business data analytics worth it ( the program has machine learning business finance and a programming course aswell )or is something general like Econ or Computers better ? I wanna do a masters afterwards most probably in Computer science or IT
Thanks for the vid, very instructive
Great visualization and explaination
that smooth music at the end really hit me
This helped a lot, thank you
His sense of humor is legendary, especially on the data logging part.
This was very helpful information; thank you!
A very good explanation on how to clarify those roles!
Amazing breakdown
Fantastic video thanks learnt soo much
Thanks for sharing. Easy to understand.
I am a marketing project manager and i was wondering if i could shift my path to data scientist/analyst, and your amazing video made it clear for me, thanks very much
Data Science/Machine Learning/Data Engineering/Data Analyst roles are incredibly overhyped and actually are not very rewarding. The competition is insane and getting a job takes almost 18 months of grinding to break into the industry. Plus you need a masters in Data Science to actually be considered for most roles. But even despite that, you are not considered for most jobs if you don't have work experience. To add on top of that, there are insanely long hours and crazy work pressure, but relatively low pay in these fields,,
You must choose your field smartly for the future -
Java and Cybersecurity roles along with, network engineer, VLSI, and networking roles are always hiring. So are, product management, Salesforce, and PPM type of roles. Core fields are great but they just aren't that much in demand. Always choose IT or CS or Electrical/Networking and learn to code in Java or Javascript. You are pretty much guaranteed to get a high-paying job.
@@mohit4902 would CIS be in this category?
@@mohit4902i was thinking of going to the data science route since my field is research but seeing your ans make me doubtful 😅😅 either way i love computers.
such a very approachable video!
The lines very easily get blurred! Thank you for the video!
The Data Science Herarchy of Needs. Excelente explicación de las diferentes necesidades y que hace cada rol en estas necesidades.
Excellent explanation
Companies nowadays prefer a generalist over a specialist who is super expert at one specific field only. This is why developers experience burn outs so often, they have almost no option but to spend a great portion of their time trying out new tech, and whatever they learn will most likely be replaced by "better" resources.
you're right, "unicorn" Data scientist is a thing now.
Most data professionals burn out even before they reach 30. But the sad part is they don't even get paid as well as quants or other similar mathematical professions do
What tip do you have for those who don't want to go through that and are finishing their graduation in Computer Science? please answer me
Awesome! thank you
the best video ever! on this topic.
Right on point , Thx.
As a software engineer I've been doing all this for 20 years, before the "analyst" position became normalize. My job title on one job was Programmer Data Analyst
Simple, concise and very good explained👍
thanks a lot for this great axplanation 🎉
AMAZING VIDEO thanx man !!!!!!!
Great explanation
well explained , thank you :)
Very easy to understand
Informative 👍🏻
Very clear!!
My fav RUclipsr is back!
Very good summarise info and helpful.
subs.. I've been seeing your video on my feed for a while now since I started roaming around to study software development but my true goal was to go up to the data scientist role, that's just the goal I have in mind and you just revealed to me that I don't exactly NEED to become a software engineer first if I can land myself to a data analyst role, the hierarchy showed me I can still walk up slowly to reaching my goal.. you are a god send.. :)
Data Science/Machine Learning/Data Engineering/Data Analyst roles are incredibly overhyped and actually are not very rewarding. The competition is insane and getting a job takes almost 18 months of grinding to break into the industry. Plus you need a masters in Data Science to actually be considered for most roles. But even despite that, you are not considered for most jobs if you don't have work experience. To add on top of that, there are insanely long hours and crazy work pressure, but relatively low pay in these fields,,
You must choose your field smartly for the future -
Java and Cybersecurity roles along with, network engineer, VLSI, and networking roles are always hiring. So are, product management, Salesforce, and PPM type of roles. Core fields are great but they just aren't that much in demand. Always choose IT or CS or Electrical/Networking and learn to code in Java or Javascript. You are pretty much guaranteed to get a high-paying job.
holy moly need more vids like this
Jesus loves you!
Thanks for the vid
Wow ty for explaining this
This is very informatif, Dude🤩
Very helpful. Thanks
Than you man
Awesome explanation, even my business analysts brain understood the difference :)
such a great video.
reading is important where ever you go
The only thing I care about when choosing between Data Scientist, Data Analyst & data Engineer is the amount of money i will get doing this job
Salary structure is like this:
Data engineer > data scientist > data analyst
@@har_d_rocks9987 Strange, I thought Data scientist would be on top
you get shitty conclusion from shitty data. Thats why data engineer more important
This was very informative
I slept for 48 hours a day and realised it was a dream 😢😢 anything is possible when you are a software engineer, Goodluck guys.
Great video
I'm studying UX and I just don't know whats going on in the engineer/developer/data world at all! Thanks for the easy to understand explainations
Thank you
Which tool you used at 3:54??
I didn’t know about this channel of you.
Tremendously helpful! Thanks!
What the difference between JomaTech and Recall by Dataiku?
very well explained
Thanks!
awesome!!
Not really, sometimes discription is just for illustration, the company will ask you to do more or sometimes not related to your scope
i didn't know joma had a second channel
Interesting. I wanted to know the difference.
“Make sure you look at the description of the job you’re applying for” 😳
really cool vid' ; thanks a lot
Where does the role of Chatgpt fit in this chart? I read that entry level data analyst tasks can now be done in seconds by Chatgpt. Please elaborate on this.
Good vide Joma :)
great video
I need to share this video. You have great content, specially for beginners like me. Thanks
Sorry for my English
25h per day could be possible if the person was traveling, some places in the word change hours when the day light is shorter or just by changing setting in the phone can eventually lead to 25h per day. But i get it, it better get rid of weird datas so it is easier to predict later
What I learned working at multiple companies is this, MOST COMPANIES DONT KNOW JACK SHIZNIT ABOUT DATA. Aside from finance & insurance companies, most places don’t have the discipline or stomach for investing in a true data first company. And that especially includes SW companies.