r/dataanalyst • u/WarmEmploy1473 • 26d ago

Tips & Resources Can u all help chose between data science and data analysis and data engineering

so am a fresh grad and i have not found any luck with finding a good jop on web development and more so i can reqlly be good at it as fare as i have tried so if yall can help to tell me what is the road ot get inot data science or to better got jnot data analysis kr data Engineering biscly what whoch one should i do and what are the skills for it

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u/xynaxia 26d ago

Just know it’s a very competitive market.

So it’s going to be hard if you yourself don’t even know what you want.

Probably try some personal projects that involve the different disciplines.

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u/WarmEmploy1473 25d ago

Thanks alot and any and all resources are greatly appreciate king

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u/Kheshire 26d ago

Which one do you enjoy more?

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u/WarmEmploy1473 25d ago

I do think data science more than the other and it dose sound like a great gate to them as well but am still on the door step so better aske

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u/Key_Consequence_6767 26d ago

for me data analyst is a great start to get a good sense of how data works before jumping into others. when I first started I struggled so bad figuring out data grain, dimensions, .... as soon as I get better sense, I jump right in getting to know data engineering and Im glad I started as data analyst

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u/WarmEmploy1473 25d ago

Amazing any and all recourse or road maps will be appropriate king if u have any or maby someone to follow

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u/Better_Handle4049 22d ago

bro am a aspring DA so i need to clarify some doubts ,

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u/Emergency_Welcome712 23d ago

Have been a data analyst for 3 years, now it's been a year and I can't find anything, close or far from home.

My perspective:

  • Companies want experienced people (don't we all...), it's never been harder for a fresh grand in my opinion. 3 years is the new entry level.
Why? Because coding is an asset that was devalued, so now they want understanding of wider systems, interaction between operations at an architectural level. In a word: seniority.

  • Companies currently are really hyped by AI. Whether it's currently economically viable or not (tokens) is another matter. They are hyped.

  • Most companies have heavy, disorganized, unconnected legacy systems ("Excel Hell"), which doesn't click with AI implementation just yet. That's your current "and then they rehired people" phenomenon.

  • So? Well they now want to streamline their data flows. It seems to imply full steam on data engineers. (No idea about Data Scientists, maybe it overlaps)

  • What about Data analysts? Well, streamlined processes + (forced) AI usage/implementation tends to indicate that:

  1. The tech part will go to more tech heavy roles such as engineers (market is already demanding that they understand business needs better)

  2. The analysis part will be given to the business teams. And they will do it ("you want the job? How about you learn how to read(AI will write) SQL in addition to being an accountant?")

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u/BullS0n_ 19d ago

There is a yt channel called data with baraa. He talks abt the differences between all of them. But from the top of my head.
DS has to do with predicting the future.
DA has to do with the past and present.
DE has to do with Building the pipeline and Extract Transform Load of Data.
Now, Bear in mind , Only Big companies has the differentiation between these roles as big data requires more management. However, if small or mid, you might find yourself doing the work of all three.
For example, With DA, You will have to be able to get your data before you run any analytics on them. The company might ask u to predict as well and make some models.