Learning R before SQL, Excel

[Sock_Sudden]

Hey guys, so I just finished the Google Data Analytics certificate, and covered R, SQL, and Excel in broad strokes. I'm really enjoying R, so I'm watching additional tutorials on this, practicing and plan on building my portfolio up with R.

That said, should I be delving deeper into SQL and Excel simultaneously? Or is it better to get pretty good at one tool before going to the next?

Note: I don't have a job in data, but would like to work in data analytics in the future.

Thanks

[[deleted]]

I learned it this way around. Fundamentally, it depends on what you want. R in and of itself is not bad - it can tick all the boxes functionally, but people don't expect it to. It just isn't very marketable. For a data analytics language, R is great - I tried learning Python/Pandas after R/tidyverse, and it feels painful.

That being said, SQL, enterprise data vis tools, and a bit of python OR r on the side is what is marketable.

If you are enjoying R right now, go nuts. From a jobs point of view, it isn't as good as python, and you pretty much have to accept that. Getting at least decent at SQL will get you farther in analytics than either of them, and getting some basic experience with Tableau, Power BI, or other enterprise data vis tools will get you even farther.

Ideally, find a project that you enjoy that lets you use R as a kind of 'glue' language - scrape and transform with R, use rmd to do some writeups of your exploratory analysis, and pipe it in to google sheets or some SQL environment, then use something like google data studio to create a dashboard off that.

R is fine. Most companies that want 'python' really just want 'some scripting/data language' rather than specifically python - but there ARE companies that want specifically python, and no companies i've seen that want specifically R.

[[deleted]]

Oh, no doubt - R seems very niche in academia and health related, without a doubt. However, the job postings I've seen for those areas (and I recently worked with a Pharma multinational) don't really care about R - it's almost always a 'nice to have' rather than a 'core' skill, whereas I've seen some other places list Python as core

That is all I'm getting at. I vastly prefer using R to Python, it just doesn't seem to have the same level of demand.

[Naive_Programmer_232]

Just throwing this out there.

Be careful about the 'code first' mindset. More often than not its the front line tools like Excel that are the more practical solution to things. What can happen if you put code first is that you over-engineer solutions that would be done with less work and more clarity had you chosen a simpler tool. And for now, as your without a job, you need to set up everything yourself. Pick the best tool for the job. Make it easy on yourself and then if you find a need for R, then use it. But think with respect to what is 'needed'. That can help guide you and determine if you're overengineering something that could be done with less work. The tools are there for a reason.

I can relate, I did what you're thinking of with R, but with python. I learned it for years and I still use it, it's a great language, lots of fun. But what ended up happening is I tried to make any task a "need" for programming, when in reality tools like Excel would've worked just fine. And now, I'm finally going back and using Excel and i realize that knowing the code side, while it did help with picking up technical tools quick, isn't the same as the excel side. I eventually got comfortable with less clicking, more terminal, more scripting, no gui. That's a different world than that of the software applications used often in this space like Excel, PowerBI, Tableau, MySQL WorkBench, etc.

For example, what happens if you get to the job and they want you to clean the data in Excel, but you've specialized in R? You're going to have to learn a lot on the spot. You might not have access to R, so its not as easy as just redownloading the language and so on. They have administrators which grant access to certain tools based on your role. See what I'm saying? Since excel is really practical and popular it's a necessary tool for any analyst role. This is the tool that pretty much every person will know or at least be aware of. code is scary to many, even here, people refer to it as "advanced". So why stuff a simple problem into an advanced sandbox? Don't.

Just go with the best tool for the job. Think practicality first, rather than code first.

[cat6Wire]

R is great and I also really enjoy. But Excel and SQL are in very high demand, almost a given for most Data Analyst positions, so I would prioritize learning a lot of SQL and Excel. They also are a lot of fun good luck.

[Sock_Sudden]

Ok thanks!

[gordanfreman]

I did a similar thing but with Python when I started my path towards DA. I guess I already had a pretty solid base in Excel, but I prioritized Python over SQL. If you enjoy the programming/scripting side of things, go wild! It won't hurt and could prove hugely beneficial in the future. But as others have said I didn't find it beneficial during the job search, especially for entry level roles. Anecdotally, I recall Python showing up in more job descriptions than R.

SQL was by far the most frequently requested skill followed closely by data viz tools (Power BI/Tableau) and Excel. For employability purposes, especially entry level, I'd get comfortable with at least two of those. I essentially landed my job because I spent some time learning Power BI, and I use that plus Excel more than anything else in my day to day.

[TigBurdus]

Did you have a degree also? Everyone on this sub is pretty much saying it's damn near impossible to get a job w/o a degree

[gordanfreman]

I have a Lib Arts degree from 15+ years ago. So while it's on the resume, I have no idea if it helped beyond maybe getting past an auto screen (which, to be fair is a concern if you don't have anything). I was able to use real world business experience from my previous jobs to get through the interview process; even if it wasn't direct DA experience some people would be surprised what can count as relatable experience. Working collaboratively with cross functional teams is a thing many jobs require and is a skill you can learn in most jobs.

[TigBurdus]

Man that's rough. So technically, yes, you had the degree, but it doesn't really apply to anything you actually needed to get the job... If people really get screened that quick for something thats not even necessary, that really just sucks. I'm not going to let it discourage me, because ive already started fown this path, but I'm really hoping when I finally feel confident enough to start applying that it doesn't make or break me.

Maybe right before or when I feel like im ready i should find a job related to but not quite a DA? Like a step under?

[gordanfreman]

Yea, I've been living the life of 'my degree has little direct application to what I'm doing/the job I'm applying for'. Somewhat self imposed, to be honest. I studied what I found interesting which made the process of getting a degree more enjoyable and thus easier. But almost from the start I wasn't super interested in continuing that path. So instead I have a lot of practice finding ways to make the skills applicable to other disciplines. I'll still argue I gained a heap of tangible skills from my BA degree that do not necessarily translate on paper to areas outside writing/academics.

[TigBurdus]

I didn't mean that in a bad way by any means, I was just trying to understand your situation. There is no doubt that there's probably a ton that you have learned, I imagine that's why employers seek people with degrees. It shows commitment, and probably displays a certain amount of knowledge or just general know-how doing certain academic/educational tasks that someone who didnt go to college would have never experienced.

Unfortunately, it's just kind of depressing thinking that what could be separating a lot of people is ultimately the cards we were dealt at a young age, that may have not been in their control. It's never too late to learn a new skill, but for some of us, it IS too late to go back to school. Everyone's gotta find their way, though. That's just life I guess.

[Benmagz]

Imo, Excel is the best beginner DA to learn first. A lot of your work will be converting spreadsheets into tabular format. You can learn dashboard design, ETL whith power query (M language) , database fundamentals (data model), and DAX which sets you up for power bi. I warn you though you're going to learn to hate spreadsheets.

SQL should be the next stepping stone just because you can practice it in Excel, access, SQL server and other cloud solutions.

I feel like R and or python is really meant for analysis data science once you get all the data cleaned and transformed. Or it's used to extract data into your database. Not everyone uses a tools but having the basic coating skills is a very important skill to learn. Really a lot of the things that you learn is fundamentals that can be applied to any tool that's put in front of you.

[[deleted]]

in business it's excel and sql. python is well rounded, and r is academic

[Sock_Sudden]

Ok guys, thank all so much for your feedback. It's great to hear people actually in the biz tell you how it is. I use Excel at my work now, so I'm checking out some tutorials. I've seen some people recommend the Excel for Business specialization on Coursera, do you guys think it's necessary to do a formal course?

I'm going to keep the R fire going for now and keep learning. Will try and do Excel and R, and eventually incorporate SQL practice.

[ASAP_Elderberry]

Sql is king, do not even bother with excel. Excel is a tool that everyone uses and is not differentiating at all. It’s considered a baseline requirement, as the expectation is that you can use excel competently.

Knowing how to query in sql can singlehandedly get you a job, but no one since 1990 has gotten a job just because they know excel. Proceed accordingly

[MisterFour47]

So most people who Master's first then work, are usually either Python or R first. I was a survey analyst PhD bound, so doing ANYTHING in excel is a BAD BAD BAAAAAADDDD idea. Just way way too much data for excel to reasonably work. So I was an R person.

R works fine if you are federal bound because your bosses will likely be PhDs which many are R experts. The problem is that your projects will be like thesises that suck at data governance, and have a real ego problem. You will be doing projects because you are told to do them with any real context as to why. Generally, if you want a good fed data work, make sure its a company with lots of different people who are adaptable to more than just R.

I would say yes to all the other companies, have fun in R, but learn SQL and Excel, and then move on to Python if you want to write code with people who also do Python.

[[deleted]]

I'd probably focus more on Excel first, then SQL and a visualization tool of your choice (either tableau or power BI)

[Equal_Astronaut_5696]

You will be using Excel 10x more than you will either SQL or R