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History? Probably should have gotten a BS in a STEM field if you wanted to go into analytics.
Thank you for your hindsight.
Until ML became accessible, 90% of analytics was reporting history. You came to the right field.
Making ties from data to major events that happened in industry or history is a essential skill. Use what you learned about history and its reteilling to make compelling arguements.
Analytics is storytelling of history, predictions on future, and arguement for outcomes. You'll do great!
Dive into some vlog or sites on working with data. Learn excel, some python, PBi, principles of unstructured data (lots of this around).
Take on some data experiments, microsoft has tons of dummy data laying around to test with.
Best regards!
Thank you!
Pick up data skills - Python, Tableau, and SQL. Look at jobs and see what tech skills they're looking for. You have to start somewhere.. and if you don't like the idea of programming, then time to reconsider what you really want.
That doesn’t dissuade me at all I would like to learn a STEM related skill.
Then learn some SQL. Gateway to programming as its will work like excel, but a bit more direct.
I would recommend doing the Google Data Analytics certification. It gives you a solid foundation and is meant for someone that doesn't have any background in data analysis. Even seasoned analysts can learn a thing or two from that program. The certification is cost effective too. It's $49 per month through Coursera. You could finish it within 3-6 months so at most this will cost you around $300. The best part is that once you are done, you will get interview and career prep, along with having access to their employer consortium. Essentially an alert will be sent out to potential employers that says you completed the certification and potential employers will want to talk to you. The US has a shortage of data analysts and data scientists so you won't have any issue landing a job. Before you ask, no I don't work for Google and this is not a paid advertisement. I've just seen it work out for a lot of people and the results speak for themselves. Check it out!
https://grow.google/certificates/data-analytics/
To my knowledge it teaches Tableau, R, and SQL along with Google Sheets.
Get a certification in Power BI through Microsoft Learn. Then apply to AFS.
Thanks!
What is your entry level analytics experience? You might not need a masters degree if you already have your foot in the door. Just try to up skill as you progress in your career!
It was mostly work with reading and analyzing contracts and working with raw data in excel and databases. Daily use of a database and excel but no use programming. I would like to increase my technical capacity and have a degree to show continued learning. I have experience analyzing data but I would like to become strong with the tools.
I’m pursuing my masters in data analytics…thank you for all of your insights
Here’s how I would approach it:
1. Study statistics - this is going to be your foundation so spend a lot of time understanding statistical concepts.
2. Learn how to code in R by performing statistical analyses.
3. Once you know R, learning Python is going to be much easier. Practice Python skills by performing exploratory data analysis. This includes cleaning data, performing statistical analyses and creating visualizations.
4. Learn the basics of SQL and learn about ETL . At this point you can pick up SQL fairly easily and you just need to know enough to select and join tables so you can retrieve the data you need. You can also practice your ETL skills using SQL.
5. Finally study data visualization best practices and pick a platform to master. I suggest Tableau or Power BI.
Tip: Don’t waste your time learning how to use Excel. All you need to know is the difference between an xlsx, csv and json file.
It's a good idea to start with learning SQL and data modeling if you want to break into Analytics. Using the Star Schema method is great for this. If your data isn't structured well, your analysis will be rough, at best. So, get to know relational datasets and how to structure and query them with SQL first. When you're comfortable with that, you can move on to visual analytics tools like Tableau or Power BI. I'd recommend starting with Tableau, though, because it's easier to learn after you've got the hang of SQL.