I would just like to know if Data Science Stack Exchange is a proper place to ask my question. I'm pasting it below.
I'm a data analyst, I studied maths and statistics and I've been working as an analyst for a year and a half. The major tools I use are R language and SQL. At the beginning I though learning Excel would be beneficial to me, so I learnt some basics of data analysis in Excel, but you know what? I find this tool useful only for these "basics". Things that are more complicated usually can be done in R more efficiently. So now I treat Excel as a little helper in glancing at the data. Then I took up Python for analysis. What happened? I got to the point where I realised that there's no thing I should do in Python instead of R, because everything doable in Python can be done in R and I can do it much faster in R, because I'm more proficient. People say Python is recommendable for machine learning stuff, but in fact it is all possible in R too.
All in all, tools are just tools. If you know what to do, you should use the tools in which you can accomplish the task in the fastest and the best way. This is a sentence which I find true and it quite discourages me from learning Python and Excel. I hardly can find anything in my job which I can't do in R.
What do I do in my job? The most of times I must answer a question about the business process of my company. I must collect data and then take insight into it - what caused the problem or when the problem existed. Unfortunately, I'm inexperienced and I can't answer these questions on the fly, without any prompt. I must know what to look for.
What I'm interested in the most is this type of task. I would like to get better at it, be more proficient in answering to such questions + convey the data better, create better plots and write more on point conclusions. But how can I do it if not by continuing working and by accomplishing new tasks? I believe it's a thing gained with experience.
What is more, there are tools which I've never seen in action. But even if I learn them, I won't become a proficient user because the only way of becoming really good is spend hours with the tool every day. I know it because I've been using R at the university for 3 years but only after first months of working I've encountered problems which were common, but totally non-existent in a theoretic world of R. What's my second problem with other tools? That in my job I don't feel I need a new tool. It's been quite proven by my Excel and Python experience too.
Of course I work with other data analysts and I could ask them. The thing is that when it comes to analysing data, they use the same tools (sometimes with lower skills in tools themselves) and I see that the only thing that distinguish our abilities is experience and intuition. As I said before, I see no way to become better at it other than just working.
My problem in a nutshell: I want to explain data better, be a better data analyst in general (in order to be paid more) but don't know what I should study. I don't feel that any new programming language will help me do it. On the other hand, if I want to work somewhere else, I should first learn some technologies that I won't use in my current workplace and it means that I won't be able to learn them well.