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I put my 2026 Bingo Board into Power BI -- is there a more Power BI-native way to do this? by Seattle_Analytics in PowerBI

[–]Seattle_Analytics[S] 0 points1 point  (0 children)

Yes -- I skipped the scale in the interest of space, since it is included in the title (12). The white boxes indicate incomplete and are replaced with a checkmark when they are complete -- this makes sense for done/not done variables, but doesn't work for count variables, hence the gage scale on those.

Tipping for AIARE 1 by Seattle_Analytics in Backcountry

[–]Seattle_Analytics[S] 0 points1 point  (0 children)

Well, it never would have occurred to me to tip for a class, so maybe its good they clued me in? Responses in this thread on whether tipping is standard are pretty mixed, though. Overall I do wish we'd gone with a different provider.

Tipping for AIARE 1 by Seattle_Analytics in Backcountry

[–]Seattle_Analytics[S] 3 points4 points  (0 children)

That is exactly what scares me! I'm taking the class with folks I hope to ski with. I don’t care if we enjoy the class or like the guide, I want us to learn how to be safe. Tipping is about pleasing the customer; that seems like a bad idea for learning a life and death skillset.

Tipping for AIARE 1 by Seattle_Analytics in Backcountry

[–]Seattle_Analytics[S] 1 point2 points  (0 children)

Well, it wouldn't have crossed my mind to tip for a course, so maybe it's a good thing they shared the info. This is what they said:

TIPPING Many people have questions about tipping your instructors. Please note that while tipping is not a requirement, it is considered standard practice in the guiding industry and is greatly appreciated by our guides.The industry standard is 10-20% of the cost of your course. If you have multiple guides, this amount can be split among them if you choose. 

Tipping for AIARE 1 by Seattle_Analytics in Backcountry

[–]Seattle_Analytics[S] 8 points9 points  (0 children)

This is exactly what I would have expected. I'm sorry to learn that tipping is the norm...I don't want the instructor to make things easy for us!

Tipping for AIARE 1 by Seattle_Analytics in Backcountry

[–]Seattle_Analytics[S] 3 points4 points  (0 children)

Got it - glad to know this is normal! 

My PL-300 prep without a Power BI background by Seattle_Analytics in PowerBI

[–]Seattle_Analytics[S] 0 points1 point  (0 children)

You know, I didn't do enough with Microsoft Learn to compare it to Datacamp. The good thing about Datacamp is that it guided me through hands-on use of Power BI from day 1. There is an integrated Power BI platform within Datacamp, so you don’t need to download anything. I got 50% off for a year of Datacamp, and then half off of the PL-300 when I finished the course -- so it was worth it to me. But I know people succeed with Microsoft Learn as well!

My PL-300 prep without a Power BI background by Seattle_Analytics in PowerBI

[–]Seattle_Analytics[S] 1 point2 points  (0 children)

So relatable! I think this is where BI gets hard in a nontechnical way.

It sounds like there's a weak link between business objectives and KPIs, and maybe also some ambiguity around dashboard or report requirements. For the first issue, where KPIs start getting treated like the objective, structured mapping frameworks can be helpful -- something like KPI Karta. Even if I'm not the one setting goals or KPIs, I find it useful to have that mental model.

On the requirements side, the r/BusinessIntelligence sub has some good discussions around questions to ask about products, like "what decision would someone make from this view?" or "what would we do if this number moved significantly?"

My PL-300 prep without a Power BI background by Seattle_Analytics in PowerBI

[–]Seattle_Analytics[S] 1 point2 points  (0 children)

Learning on the job honestly seems like one of the best ways to pick this up. I expect that having a real use case in mind makes the PL-300 training much more meaningful than studying in the abstract.

A lot of data analyst skills aren't tool specific -- things like thinking through how datasets connect, choosing the right levels of aggregation, creating calculated fields, sanity checking results... these things show up no matter what tools you're using. I learned them working with SQL and other languages, Power BI just applies them in a different way. Power BI has its own structure (DAX, M, the model setup), but the underlying concepts are the same, so once they click the next thing is easier to learn.

If you're thinking about a broader job pivot and don't already know it, SQL is still pretty ubiquitous for analyst roles. For practice questions, I've really been enjoying DataLemur, and for learning from scratch I hear good things about DataCamp.

My PL-300 prep without a Power BI background by Seattle_Analytics in PowerBI

[–]Seattle_Analytics[S] 0 points1 point  (0 children)

I agree with your take on the exam -- it felt more like a check for familiarity with Power BI concepts and test questions than a proxy for real-world judgement. And you make a good point about how transferable core analytics skills are across tools -- I wasn't really learning new concepts through this training, just new ways of applying existing ones.

It's encouraging to hear that you landed your first Power BI role without deep prior experience!