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Seeking advice re learning the basics of data analytics
I was contacted by a recruiter regarding a job in my field but they wanted someone with data analytics skills. I'm taking this as a sign that I should improve my skill set. Does anyone have advice for where or how to start with a very small budget?
Thanks for your help.
I'm a data scientist. Over the years I've had titles including: reporting analyst, business intelligence analyst, data visualization specialist, data engineer, and data architect. The field is broad and there are a lot of different skills that can be considered to exist under data analytics.
My experience with recruiters and job postings is that if they're asking broad questions like "data analytics" they're generally looking for skills in the following tools/languages: SQL, Excel, and Data Visualization.
If they use words like architect or engineer they're looking for more programming and DB experience - SQL, R, Python, DBA stuff.
If they use words like data science or ML/AI then they're generally looking for ML/AI skills even if it's not the bulk of what you do.
Absolutely none of these require a budget. Plenty of online SQL classes and resources, plenty of youtube videos on excel, you can go download a trial copy of tableau and get public data trivially, etc. Frankly just find some online free data sets or training on excel or SQL or look for data challenges that exist out there and start digging into the data with basic tools. It's a bit more involved to get into the data science realm as it requires some understanding of statistics and some programming skills in R or Python (generally speaking) but that's not really a starting point and not what people are generally looking for when they say "analytics" unless it's a job in finance.
There's nothing like actually doing it. I'd recommend going on kaggle and participating in some competitions. A classic beginner one is the titanic dataset: https://www.kaggle.com/competitions/titanic
Not only is it good practice, but you can learn a lot from other people's submissions, on what techniques they use, and why.
It's a broad field. It could mean being good at Excel, being able to write database queries, using R or Python to analyze scientific data, building machine learning pipelines, or something else entirely. There are lots of tools, and the job will probably require learning the tools that they use at a particular company.
You might be able to get some idea from the job postings you're interested in, though?
Whatever you're trying to learn, it's likely to be more about spending time than money, because there's so much free educational material out there on the Internet. The question is what to focus on.