Hey GOATs Community, after almost 10 years in sales I found my passion in data analysis (or related to that) and like to start. However, I do not know where ro begin. What learing courses fit and are recognized by employers?
So far, I’m learing Phyton and thinking about starting the Google or IBM Data Analysis course. But when is someone ready to build a portfolio? What is the timeline to apply to a first job? How long does it take to be ready, if I work fulltime?
Thanks for your help 
Hey @Alecksis - this might be a good place to start: A Comprehensive Analyst’s Guide to Career Resources (2025) - it’s from our blog here.
I personally think someone should learn Excel & SQL first. They are the most commonly used tools in analytics. I would consider mastery in those first as a good first step. After that, Python is an incredible tool. I use it regularly and think it has some awesome use cases. That said, if you have already started using Python, don’t abandon it, I would just make sure to focus on Excel & SQL as an absolute first.
Then, I would consider getting some strength in a BI tool. Since Tableau Public is free, that’s a good one to use. A lot of companies use Tableau. Power BI is another one that’s great.
I’d say you can start applying to entry level roles once you feel comfortable in that basic set of skills above. It’s competitive, so it may take some time to land that first role. You can be practicing and mastering all while doing that. For your portfolio, I’d try to use some real world projects - think “How can I identify a problem that’s meaningful, and use data to solve it?”
I’d also be happy to chat about all of this if you would like to go any deeper into any of the topics.. either on this thread or feel free to send me a message!
Excel is an excellent place to start as many jobs in and outside of data analytics will use some form of spreadsheet.
I’m actually taking a Power Query course through Maven Analytics. One thing I did learn is that there is a limit to the number of rows a dataset can have if loading it into Excel, but with Power Query you can have a dataset with millions of rows, but it’s different than being a traditional spreadsheet. Nonetheless, it shows the power Excel can have if you know more of the advanced tools.
As for projects; for your first one find any real world dataset if you can and try and simulate what kinds questions might be asked by management/stakeholders. Then I would start focusing on domain specific projects: Healthcare, financial, retail, accounting, city planning, or other domains.
I love the advice of focusing on a domain project. Building some domain specific knowledge is really useful.
Power Query is really useful. I used it a bit in my last job using ODBC to refresh some cloud saved workbooks we used for a Power Automate flow + SharePoint integration. It wasn’t the cleanest solution but it enabled a pretty important project to scale without a big systems investment.
Interesting timing, I just found this video from a LinkedIn contact and thought it would be beneficial.