Hey there, everybody. Recent joiner who’s been lurking. I have been searching the posts here and gotten some great info from them, but I’ve now got some questions of my own. Hopefully, they’re ones that others have and they might benefit from the thread, as well.

TL;DR: I feel like I need more skills to apply for new positions, and I don’t know which skills to learn or the best places to cultivate them that an employer would recognize as legitimate.

I am currently working as a Data Analyst (though that title is a reach, you’ll see why below) since Spring of 2022. It’s my first corporate position, though not close to my first work experience, and I have advanced very quickly. I am in line for my second promotion right now, depending on the completion of some goals. The trouble is, this company fucking sucks. It’s a mess at every level. I am one of the most competent people on my team “data analytics” wise, and some of these people have been here for the better part of a decade. I really don’t say that to make myself sound like some sort of savant, but to highlight just how poor the standards of quality and skill are. Our R&D department is basically one guy whose file organization is about as clear as muck. All it took to be a walk-on was some creativity and a VERY baseline understanding of computers.

All of this to say that I do not have the same industry skills as other data analysts. My team is really pigeon-holed in the scope of what we do. Without giving away too much detail, it’s basically just bioinformatics quality assurance. So the softwares I now know, and the processes I have learned, are largely industry and company specific. I opted to teach myself Excel macro construction to make my own life easier. I’m only one of two out of 15 people on my team that knows how to make them. All of it is self study. I can’t go to anyone at my company, because they don’t know anything, either. They don’t even “allow” us to use SQL, and the data we produce is far, far too large for Excel.

I am currently finishing up the Google Data Analytics Certificate on Coursera. But I don’t feel that any of it is enough when I read these job ads. There’s another course that follows this one, but I’m thinking that I’d rather pivot to data science. That just leaves me with more uncertainty on which skills to invest in.

All this to ask: once I’ve completed the Data Analytics cert, what do next? Those boot camps don’t seem worth it price wise, and I imagine that workforce is very saturated. I have considered applying to graduate programs for bioinformatics, but I’m on the fence about returning to academia unless I can get some sort of grant, and that’s so competitive these days I’m not sure if I will outshine other candidates. I have some experience in JS. I am learning Python, R, and SQL. I have ordered the book “Automate the Boring Stuff” for my python learning, too.

Once I decide what to do, it’ll be easy. I’m very good at learning these things and solving my own issues as I learn (which is most computer shit anyways). The problem I have is that I just don’t feel like I have a good read on the industry outside of the very small corner I’m in.

Thank you in advance. Sorry that got so long-winded.

  • Arotrios@kbin.social
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    1 year ago

    I would advise staying away from academia and niche industries - you’re going to be criminally underpaid. A data analyst with 3+ years experience can command 100k easily working from home for a mid to large scale e-commerce shop if you have SQL chops. I saw a jump of 50% in salary when I moved from a niche industry into standard e-commerce.

    I haven’t done the certificate with Coursera, so I’m not sure what’s covered there, but one of the biggest challenges facing the e-commerce industry right now is the migration from Universal Analytics to Google Analytics 4. If you can master that process (which is like riding an epileptic horse on PCP), you’ll have no end of career opportunities.

    I’d recommend getting up to date with Google’s Looker Studio - it’s free and the capacities greatly exceed GA4’s standard interface (which is a downgrade from the Universal Analytics interface IMHO). R’s Google Analytics library is also extremely useful as you can export data without sampling, and you can test and write out your queries in Google’s Query Explorer before tying up your machine with a big export. Here’s the link on the CRAN site to the R library.

    If you have the opportunity, I’d also learn Amazon’s Quicksight, which is absolutely fantastic. They allow you to build table joins from within the interface from full table pulls, so it doesn’t require advanced SQL knowledge to bring forth reports. They also provide object-oriented calculations, which can be engaged with their built-in machine learning to pull forecasts.

    Context: 20+ years experience doing this shit.

    • morg@programming.devOP
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      1 year ago

      Thank you! I will look into Google Analytics and Looker Studio, and Quicksight.

      I haven’t done anything with like any of what you mentioned. That’s how niched I am right now. It’s ridiculous. The common sense things in the basic Google cert is far and above the capabilities of my current team in an appalling way. Not surprisingly, my salary is garbage. My priority for the last months has been making myself hireable somewhere else.

      Do data analytics positions normally do a skill interview? How common is on the job training for a junior/lower mid level position when you onboard? I have plenty of experience teaching myself what I’m supposed to be doing, but having some skill transfer is much less stressful.

      • Arotrios@kbin.social
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        1 year ago

        It depends on the team you’re applying to. Marketing teams are much more relaxed about the skill set, and are more interested in the story you can tell with the data you pull. If you’re applying for a backend position, where you’re doing ETL operations (extract, transform, load) you’re going to get much more technical questions, particularly as it relates to SQL. That being said, the backend positions are much more stable employment wise than working on a marketing team. In general, I’ve found that most employers are less interested in the technical basics (which can be taught) than what your development skills brought to your last position, and your desire to learn. Self-directed learning is generally very highly respected, and your cert will definitely help.

        I wouldn’t expect much on the job training - generally the seniors will expect you to learn through solving the problems they give you to fix, or you’ll be the one data analyst expected to figure out the incoming data. Imposter syndrome is somewhat common amongst analysts as a result - it’s easy to feel like you don’t know what you’re doing, even when it works.

        I went back over your post, and I’d say at this point, focus on SQL even if your work won’t allow you to use it directly. It’s pretty easy to learn, and getting the basics down will significantly increase your employment chances.

        Regarding your Excel limits issue, look into using the Data Model - it can hold far more data than a standard sheet (10mil+ rows with ease if your computer has the juice to parse it), as well as having relational database capacity between linked tables (that far exceed a lookup formula). I used this at my last job to build an inventory tracking system when Microsoft Nav decided to shit the bed, and with Power Query, Excel was able to perform SQL pulls from within the sheet with an ODBC connection to the database.

        • morg@programming.devOP
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          1 year ago

          That Data Model tool is going to be an absolute game changer. Bless you. I can think of at least three use cases in my current system that need this desperately.

          I’m going to make myself a little pet project to work more in BigQuery and make my own queries, outside of what the cert has had me doing. The last part of the cert is a case study type project, so I will at least have something to accompany my resume once I start applying.

          Also, no kidding about the imposter syndrome. I’m in this weird limbo feeling like I’m being gaslit at work about what I know and don’t know just because no one around me knows what I’m doing. We’re all animal science/biology majors, but everyone else has more lab experience. They claim to want people that understand the chemistry, but I don’t have any clue to it and I am now basically a team and product lead with the computer and analytical skills alone.

          • Arotrios@kbin.social
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            1 year ago

            Cool! Glad it helps! One important thing to note is that the Data Model uses not Visual Basic, but DAX as its syntax. It’s considerably more powerful than - but similar to - VB. It should be easy for you to learn.

            Once your data chops are strong enough, it doesn’t matter whether you’re doing biology or e-commerce in this field - it’s all about how well you work with the information. I’m not surprised you got team lead given your self-directed nature and aptitude for this work. In fact, with your current experience, you’ll have a leg up, as analysts who work in your field are highly regarded. I think you’re well on your way - good luck!

            • morg@programming.devOP
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              1 year ago

              I don’t even know much VBA (wrote my macros in visual studio using the record macro tool to help me teach myself while I built), so DAX shouldn’t be too jarring!

              All this definitely makes me feel better. I actually really enjoy this type of stuff. Working with the data has been really cool and I love learning the new skills. I want a job where I can keep doing that instead of just being a data monkey locked at a 3% increase every year with no bonus.

  • Reader9@programming.dev
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    1 year ago

    I am learning Python, R, and SQL

    SQL is an excellent skill to invest in. Even though your current role doesn’t allow you to use it, there’s no substitute when pulling data from a relational db.

    It sounds like you’re currently focused on data quality. Automatic data quality checks are common features of (good) data workflows so this could be spun as relevant experience if you end up seeking a role writing data transformation code.

  • neil@programming.dev
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    1 year ago

    Like others said: sql, sql, sql. The syntax is probably easier than excel, but a lot of people stink at it because they don’t want to invest in the spatial reasoning required to make it work magic, and that opens doors to easy opportunity.

    If you can get into a position like reporting or data quality, and be “that person” that fixes a dreaded slow query to make it run in milliseconds instead of minutes, then you’ll get your proverbial blank check to go where you want. Those queries exist in just about every business.

    Take a look around for “sql portfolio projects” for more complete stuff that goes beyond tutorials.

    • morg@programming.devOP
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      1 year ago

      the SQL syntax is certainly very straightforward. It’s funny, I find excel really fun to work with. Maybe that’s the Stockholm Syndrome of it being the only tool I’m really capable of applying at work 😅

  • ericjmorey@programming.devM
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    1 year ago

    If you’re not already aware of Kaggle, you should use the data they have there to practice.

    They also have some solid hands on learning resources that will likely be better for you that Automate the Boring Stuff since it focuses on data analysis using Python and related Python libraries.

    • morg@programming.devOP
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      1 year ago

      Yep! I’ve got an account. I really need to give the site a deep dive though and see everything it has to offer.

  • Unquote0270@programming.dev
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    1 year ago

    My advice is to just apply and if it takes a while then keep learning and practicing what you know. I was in a similar position and decided to learn python to automate stuff in my admin job. The job was fairly data centric so it wasn’t long until I saw someone using pandas and I instantly knew I wanted to be an analyst. I spent a while learning pandas, then SQL and then dicked around with power bi a bit.

    When I started applying for jobs I didn’t have much success at first but I stumbled on one which included tools I had no experience with but I applied anyway, not expecting anything but feeling desperate and hopeless at that point. Well, I heard back from this one and I ended up getting the job somehow. Now I use Alteryx, which I had never heard of, and Tableau, which I had never used. They must have seen that I was passionate and loved to learn, and we’re happy to take me on based on the potential I had. I rarely use python or pandas, occasionally SQL for basic stuff, so it was more the principles from learning these that were useful rather than the actual tools themselves.

    I would recommend learning at least the basics of SQL and start learning tableau (by using tableau public). Most of the skills are transferable so learning the logic of one programming language and a bi tool will mean that you can pick up others fairly easily and employers understand this. If you are in excel a lot then learn how to write formulas and learn power query so you can practice joins and data cleansing.

    So basically, get the fundamentals down and start applying, don’t spend forever trying to learn a million things because you think they are all essential. Apply for as many jobs as you can, even if you don’t know the tools they use, and practice and develop your skills while you are waiting.

    • morg@programming.devOP
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      1 year ago

      I think that’s where I’m at. I just need to update the resume and start putting it out there while I work. I have done some work with Tableau, and I already see how much potential it has. I definitely have the least amount of experience with viz as my customers are all researchers or labs that want raw data.